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Smart Resume AI - Main Application
"""
import time
from PIL import Image
from jobs.job_search import render_job_search
from datetime import datetime
from ui_components import (
apply_modern_styles, hero_section, feature_card, about_section,
page_header, render_analytics_section, render_activity_section,
render_suggestions_section
)
from feedback.feedback import FeedbackManager
from docx.enum.text import WD_ALIGN_PARAGRAPH
from docx.shared import Inches, Pt
from docx import Document
import io
import base64
import plotly.graph_objects as go
from streamlit_lottie import st_lottie
import requests
from dashboard.dashboard import DashboardManager
from config.courses import COURSES_BY_CATEGORY, RESUME_VIDEOS, INTERVIEW_VIDEOS, get_courses_for_role, get_category_for_role
from config.job_roles import JOB_ROLES
from config.database import (
get_database_connection, save_resume_data, save_analysis_data,
init_database, verify_admin, log_admin_action, save_ai_analysis_data,
get_ai_analysis_stats, reset_ai_analysis_stats, get_detailed_ai_analysis_stats
)
from utils.ai_resume_analyzer import AIResumeAnalyzer
from utils.resume_builder import ResumeBuilder
from utils.resume_analyzer import ResumeAnalyzer
import traceback
import plotly.express as px
import pandas as pd
import json
import streamlit as st
import datetime
# Set page config at the very beginning
st.set_page_config(
page_title="Smart Resume AI",
page_icon="🚀",
layout="wide"
)
class ResumeApp:
def __init__(self):
"""Initialize the application"""
if 'form_data' not in st.session_state:
st.session_state.form_data = {
'personal_info': {
'full_name': '',
'email': '',
'phone': '',
'location': '',
'linkedin': '',
'portfolio': ''
},
'summary': '',
'experiences': [],
'education': [],
'projects': [],
'skills_categories': {
'technical': [],
'soft': [],
'languages': [],
'tools': []
}
}
# Initialize navigation state
if 'page' not in st.session_state:
st.session_state.page = 'home'
# Initialize admin state
if 'is_admin' not in st.session_state:
st.session_state.is_admin = False
self.pages = {
"🏠 HOME": self.render_home,
"🔍 RESUME ANALYZER": self.render_analyzer,
"📝 RESUME BUILDER": self.render_builder,
"📊 DASHBOARD": self.render_dashboard,
"🎯 JOB SEARCH": self.render_job_search,
"💬 FEEDBACK": self.render_feedback_page,
"ℹ️ ABOUT": self.render_about
}
# Initialize dashboard manager
self.dashboard_manager = DashboardManager()
self.analyzer = ResumeAnalyzer()
self.ai_analyzer = AIResumeAnalyzer()
self.builder = ResumeBuilder()
self.job_roles = JOB_ROLES
# Initialize session state
if 'user_id' not in st.session_state:
st.session_state.user_id = 'default_user'
if 'selected_role' not in st.session_state:
st.session_state.selected_role = None
# Initialize database
init_database()
# Load external CSS
with open('style/style.css') as f:
st.markdown(f'<style>{f.read()}</style>', unsafe_allow_html=True)
# Load Google Fonts
st.markdown("""
<link href="https://fonts.googleapis.com/css2?family=Roboto:wght@400;500;700&family=Poppins:wght@400;500;600&display=swap" rel="stylesheet">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.15.4/css/all.min.css">
""", unsafe_allow_html=True)
if 'resume_data' not in st.session_state:
st.session_state.resume_data = []
if 'ai_analysis_stats' not in st.session_state:
st.session_state.ai_analysis_stats = {
'score_distribution': {},
'total_analyses': 0,
'average_score': 0
}
def load_lottie_url(self, url: str):
"""Load Lottie animation from URL"""
r = requests.get(url)
if r.status_code != 200:
return None
return r.json()
def apply_global_styles(self):
st.markdown("""
<style>
/* Custom Scrollbar */
::-webkit-scrollbar {
width: 8px;
height: 8px;
}
::-webkit-scrollbar-track {
background: #1a1a1a;
border-radius: 4px;
}
::-webkit-scrollbar-thumb {
background: #4CAF50;
border-radius: 4px;
}
::-webkit-scrollbar-thumb:hover {
background: #45a049;
}
/* Global Styles */
.main-header {
background: linear-gradient(135deg, #4CAF50 0%, #45a049 100%);
padding: 2rem;
border-radius: 15px;
margin-bottom: 2rem;
box-shadow: 0 10px 20px rgba(0,0,0,0.2);
text-align: center;
position: relative;
overflow: hidden;
}
.main-header::before {
content: '';
position: absolute;
top: 0;
left: 0;
width: 100%;
height: 100%;
background: linear-gradient(45deg, transparent 0%, rgba(255,255,255,0.1) 100%);
z-index: 1;
}
.main-header h1 {
color: white;
font-size: 2.5rem;
font-weight: 600;
margin: 0;
position: relative;
z-index: 2;
}
/* Template Card Styles */
.template-container {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(320px, 1fr));
gap: 2rem;
padding: 1rem;
}
.template-card {
background: rgba(45, 45, 45, 0.9);
border-radius: 20px;
padding: 2rem;
position: relative;
overflow: hidden;
backdrop-filter: blur(10px);
border: 1px solid rgba(255,255,255,0.1);
transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1);
}
.template-card:hover {
transform: translateY(-10px);
box-shadow: 0 20px 40px rgba(0,0,0,0.3);
border-color: #4CAF50;
}
.template-card::before {
content: '';
position: absolute;
top: 0;
left: 0;
width: 100%;
height: 100%;
background: linear-gradient(45deg, transparent 0%, rgba(76,175,80,0.1) 100%);
z-index: 1;
}
.template-icon {
font-size: 3rem;
color: #4CAF50;
margin-bottom: 1.5rem;
position: relative;
z-index: 2;
}
.template-title {
font-size: 1.8rem;
font-weight: 600;
color: white;
margin-bottom: 1rem;
position: relative;
z-index: 2;
}
.template-description {
color: #aaa;
margin-bottom: 1.5rem;
position: relative;
z-index: 2;
line-height: 1.6;
}
/* Feature List Styles */
.feature-list {
list-style: none;
padding: 0;
margin: 1.5rem 0;
position: relative;
z-index: 2;
}
.feature-item {
display: flex;
align-items: center;
margin-bottom: 1rem;
color: #ddd;
font-size: 0.95rem;
}
.feature-icon {
color: #4CAF50;
margin-right: 0.8rem;
font-size: 1.1rem;
}
/* Button Styles */
.action-button {
background: linear-gradient(135deg, #4CAF50 0%, #45a049 100%);
color: white;
padding: 1rem 2rem;
border-radius: 50px;
border: none;
font-weight: 500;
cursor: pointer;
width: 100%;
text-align: center;
position: relative;
overflow: hidden;
z-index: 2;
transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1);
}
.action-button:hover {
transform: translateY(-2px);
box-shadow: 0 10px 20px rgba(76,175,80,0.3);
}
.action-button::before {
content: '';
position: absolute;
top: 0;
left: -100%;
width: 100%;
height: 100%;
background: linear-gradient(90deg, transparent 0%, rgba(255,255,255,0.2) 50%, transparent 100%);
transition: all 0.6s ease;
}
.action-button:hover::before {
left: 100%;
}
/* Form Section Styles */
.form-section {
background: rgba(45, 45, 45, 0.9);
border-radius: 20px;
padding: 2rem;
margin: 2rem 0;
backdrop-filter: blur(10px);
border: 1px solid rgba(255,255,255,0.1);
}
.form-section-title {
font-size: 1.8rem;
font-weight: 600;
color: white;
margin-bottom: 1.5rem;
padding-bottom: 0.8rem;
border-bottom: 2px solid #4CAF50;
}
.form-group {
margin-bottom: 1.5rem;
}
.form-label {
color: #ddd;
font-weight: 500;
margin-bottom: 0.8rem;
display: block;
}
.form-input {
width: 100%;
padding: 1rem;
border-radius: 10px;
border: 1px solid rgba(255,255,255,0.1);
background: rgba(30, 30, 30, 0.9);
color: white;
transition: all 0.3s ease;
}
.form-input:focus {
border-color: #4CAF50;
box-shadow: 0 0 0 2px rgba(76,175,80,0.2);
outline: none;
}
/* Skill Tags */
.skill-tag-container {
display: flex;
flex-wrap: wrap;
gap: 0.8rem;
margin-top: 1rem;
}
.skill-tag {
background: rgba(76,175,80,0.1);
color: #4CAF50;
padding: 0.6rem 1.2rem;
border-radius: 50px;
border: 1px solid #4CAF50;
font-size: 0.9rem;
transition: all 0.3s ease;
cursor: pointer;
}
.skill-tag:hover {
background: #4CAF50;
color: white;
transform: translateY(-2px);
box-shadow: 0 5px 15px rgba(76,175,80,0.2);
}
/* Progress Circle */
.progress-container {
position: relative;
width: 150px;
height: 150px;
margin: 2rem auto;
}
.progress-circle {
transform: rotate(-90deg);
width: 100%;
height: 100%;
}
.progress-circle circle {
fill: none;
stroke-width: 8;
stroke-linecap: round;
stroke: #4CAF50;
transform-origin: 50% 50%;
transition: all 0.3s ease;
}
.progress-text {
position: absolute;
top: 50%;
left: 50%;
transform: translate(-50%, -50%);
font-size: 1.5rem;
font-weight: 600;
color: white;
}
.main .block-container {
padding-top: 2rem;
padding-bottom: 2rem;
}
.feature-card {
background-color: #1e1e1e;
border-radius: 10px;
padding: 20px;
margin-bottom: 20px;
box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
}
/* Animations */
@keyframes slideIn {
from {
opacity: 0;
transform: translateY(30px);
}
to {
opacity: 1;
transform: translateY(0);
}
}
.animate-slide-in {
animation: slideIn 0.6s cubic-bezier(0.4, 0, 0.2, 1) forwards;
}
/* Responsive Design */
@media (max-width: 768px) {
.template-container {
grid-template-columns: 1fr;
}
.main-header {
padding: 1.5rem;
}
.main-header h1 {
font-size: 2rem;
}
.template-card {
padding: 1.5rem;
}
.action-button {
padding: 0.8rem 1.6rem;
}
}
</style>
""", unsafe_allow_html=True)
def add_footer(self):
"""Add a footer to all pages"""
st.markdown("<hr style='margin-top: 50px; margin-bottom: 20px;'>", unsafe_allow_html=True)
col1, col2, col3 = st.columns([1, 3, 1])
with col2:
# GitHub star button with lottie animation
st.markdown("""
<div style='display: flex; justify-content: center; align-items: center; margin-bottom: 10px;'>
<a href='https://github.com/babaiii07' target='_blank' style='text-decoration: none;'>
<div style='display: flex; align-items: center; background-color: #24292e; padding: 5px 10px; border-radius: 5px; transition: all 0.3s ease;'>
<svg height="16" width="16" viewBox="0 0 16 16" version="1.1" style='margin-right: 5px;'>
<path fill-rule="evenodd" d="M8 .25a.75.75 0 01.673.418l1.882 3.815 4.21.612a.75.75 0 01.416 1.279l-3.046 2.97.719 4.192a.75.75 0 01-1.088.791L8 12.347l-3.766 1.98a.75.75 0 01-1.088-.79l.72-4.194L.818 6.374a.75.75 0 01.416-1.28l4.21-.611L7.327.668A.75.75 0 018 .25z" fill="gold"></path>
</svg>
<span style='color: white; font-size: 14px;'>Star this repo</span>
</div>
</a>
</div>
""", unsafe_allow_html=True)
# Footer text
st.markdown("""
<p style='text-align: center;'>
Powered by <b>Streamlit</b> and <b>Groq Llama 3.3 70B</b> | Developed by
<a href="https://www.linkedin.com/in/parthib-karak-9a0bb1286" target="_blank" style='text-decoration: none; color: #FFFFFF'>
<b>Parthib karak</b>
</a>
</p>
<p style='text-align: center; font-size: 12px; color: #888888;'>
"Every star counts! If you find this project helpful, please consider starring the repo to help it reach more people."
</p>
""", unsafe_allow_html=True)
def load_image(self, image_name):
"""Load image from static directory"""
try:
image_path = f"c:/Users/shree/Downloads/smart-resume-ai/{image_name}"
with open(image_path, "rb") as f:
image_bytes = f.read()
encoded = base64.b64encode(image_bytes).decode()
return f"data:image/png;base64,{encoded}"
except Exception as e:
print(f"Error loading image {image_name}: {e}")
return None
def export_to_excel(self):
"""Export resume data to Excel"""
conn = get_database_connection()
# Get resume data with analysis
query = """
SELECT
rd.name, rd.email, rd.phone, rd.linkedin, rd.github, rd.portfolio,
rd.summary, rd.target_role, rd.target_category,
rd.education, rd.experience, rd.projects, rd.skills,
ra.ats_score, ra.keyword_match_score, ra.format_score, ra.section_score,
ra.missing_skills, ra.recommendations,
rd.created_at
FROM resume_data rd
LEFT JOIN resume_analysis ra ON rd.id = ra.resume_id
"""
try:
# Read data into DataFrame
df = pd.read_sql_query(query, conn)
# Create Excel writer object
output = io.BytesIO()
with pd.ExcelWriter(output, engine='openpyxl') as writer:
df.to_excel(writer, index=False, sheet_name='Resume Data')
return output.getvalue()
except Exception as e:
print(f"Error exporting to Excel: {str(e)}")
return None
finally:
conn.close()
def render_dashboard(self):
"""Render the dashboard page"""
self.dashboard_manager.render_dashboard()
st.toast("Check out these repositories: [Awesome Hacking](https://github.com/Hunterdii/Awesome-Hacking)", icon="ℹ️")
def render_empty_state(self, icon, message):
"""Render an empty state with icon and message"""
return f"""
<div style='text-align: center; padding: 2rem; color: #666;'>
<i class='{icon}' style='font-size: 2rem; margin-bottom: 1rem; color: #00bfa5;'></i>
<p style='margin: 0;'>{message}</p>
</div>
"""
def analyze_resume(self, resume_text):
"""Analyze resume and store results"""
analytics = self.analyzer.analyze_resume(resume_text)
st.session_state.analytics_data = analytics
return analytics
def handle_resume_upload(self):
"""Handle resume upload and analysis"""
uploaded_file = st.file_uploader(
"Upload your resume", type=['pdf', 'docx'])
if uploaded_file is not None:
try:
# Extract text from resume
if uploaded_file.type == "application/pdf":
resume_text = extract_text_from_pdf(uploaded_file)
else:
resume_text = extract_text_from_docx(uploaded_file)
# Store resume data
st.session_state.resume_data = {
'filename': uploaded_file.name,
'content': resume_text,
'upload_time': datetime.now().isoformat()
}
# Analyze resume
analytics = self.analyze_resume(resume_text)
return True
except Exception as e:
st.error(f"Error processing resume: {str(e)}")
return False
return False
def render_builder(self):
st.title("Resume Builder 📝")
st.write("Create your professional resume")
# Template selection
template_options = ["Modern", "Professional", "Minimal", "Creative"]
selected_template = st.selectbox(
"Select Resume Template", template_options)
st.success(f"🎨 Currently using: {selected_template} Template")
# Personal Information
st.subheader("Personal Information")
col1, col2 = st.columns(2)
with col1:
# Get existing values from session state
existing_name = st.session_state.form_data['personal_info']['full_name']
existing_email = st.session_state.form_data['personal_info']['email']
existing_phone = st.session_state.form_data['personal_info']['phone']
# Input fields with existing values
full_name = st.text_input("Full Name", value=existing_name)
email = st.text_input(
"Email",
value=existing_email,
key="email_input")
phone = st.text_input("Phone", value=existing_phone)
# Immediately update session state after email input
if 'email_input' in st.session_state:
st.session_state.form_data['personal_info']['email'] = st.session_state.email_input
with col2:
# Get existing values from session state
existing_location = st.session_state.form_data['personal_info']['location']
existing_linkedin = st.session_state.form_data['personal_info']['linkedin']
existing_portfolio = st.session_state.form_data['personal_info']['portfolio']
# Input fields with existing values
location = st.text_input("Location", value=existing_location)
linkedin = st.text_input("LinkedIn URL", value=existing_linkedin)
portfolio = st.text_input(
"Portfolio Website", value=existing_portfolio)
# Update personal info in session state
st.session_state.form_data['personal_info'] = {
'full_name': full_name,
'email': email,
'phone': phone,
'location': location,
'linkedin': linkedin,
'portfolio': portfolio
}
# Professional Summary
st.subheader("Professional Summary")
summary = st.text_area("Professional Summary", value=st.session_state.form_data.get('summary', ''), height=150,
help="Write a brief summary highlighting your key skills and experience")
# Experience Section
st.subheader("Work Experience")
if 'experiences' not in st.session_state.form_data:
st.session_state.form_data['experiences'] = []
if st.button("Add Experience"):
st.session_state.form_data['experiences'].append({
'company': '',
'position': '',
'start_date': '',
'end_date': '',
'description': '',
'responsibilities': [],
'achievements': []
})
for idx, exp in enumerate(st.session_state.form_data['experiences']):
with st.expander(f"Experience {idx + 1}", expanded=True):
col1, col2 = st.columns(2)
with col1:
exp['company'] = st.text_input(
"Company Name",
key=f"company_{idx}",
value=exp.get(
'company',
''))
exp['position'] = st.text_input(
"Position", key=f"position_{idx}", value=exp.get(
'position', ''))
with col2:
exp['start_date'] = st.text_input(
"Start Date", key=f"start_date_{idx}", value=exp.get(
'start_date', ''))
exp['end_date'] = st.text_input(
"End Date", key=f"end_date_{idx}", value=exp.get(
'end_date', ''))
exp['description'] = st.text_area("Role Overview", key=f"desc_{idx}",
value=exp.get(
'description', ''),
help="Brief overview of your role and impact")
# Responsibilities
st.markdown("##### Key Responsibilities")
resp_text = st.text_area("Enter responsibilities (one per line)",
key=f"resp_{idx}",
value='\n'.join(
exp.get('responsibilities', [])),
height=100,
help="List your main responsibilities, one per line")
exp['responsibilities'] = [r.strip()
for r in resp_text.split('\n') if r.strip()]
# Achievements
st.markdown("##### Key Achievements")
achv_text = st.text_area("Enter achievements (one per line)",
key=f"achv_{idx}",
value='\n'.join(
exp.get('achievements', [])),
height=100,
help="List your notable achievements, one per line")
exp['achievements'] = [a.strip()
for a in achv_text.split('\n') if a.strip()]
if st.button("Remove Experience", key=f"remove_exp_{idx}"):
st.session_state.form_data['experiences'].pop(idx)
st.rerun()
# Projects Section
st.subheader("Projects")
if 'projects' not in st.session_state.form_data:
st.session_state.form_data['projects'] = []
if st.button("Add Project"):
st.session_state.form_data['projects'].append({
'name': '',
'technologies': '',
'description': '',
'responsibilities': [],
'achievements': [],
'link': ''
})
for idx, proj in enumerate(st.session_state.form_data['projects']):
with st.expander(f"Project {idx + 1}", expanded=True):
proj['name'] = st.text_input(
"Project Name",
key=f"proj_name_{idx}",
value=proj.get(
'name',
''))
proj['technologies'] = st.text_input("Technologies Used", key=f"proj_tech_{idx}",
value=proj.get(
'technologies', ''),
help="List the main technologies, frameworks, and tools used")
proj['description'] = st.text_area("Project Overview", key=f"proj_desc_{idx}",
value=proj.get(
'description', ''),
help="Brief overview of the project and its goals")
# Project Responsibilities
st.markdown("##### Key Responsibilities")
proj_resp_text = st.text_area("Enter responsibilities (one per line)",
key=f"proj_resp_{idx}",
value='\n'.join(
proj.get('responsibilities', [])),
height=100,
help="List your main responsibilities in the project")
proj['responsibilities'] = [r.strip()
for r in proj_resp_text.split('\n') if r.strip()]
# Project Achievements
st.markdown("##### Key Achievements")
proj_achv_text = st.text_area("Enter achievements (one per line)",
key=f"proj_achv_{idx}",
value='\n'.join(
proj.get('achievements', [])),
height=100,
help="List the project's key achievements and your contributions")
proj['achievements'] = [a.strip()
for a in proj_achv_text.split('\n') if a.strip()]
proj['link'] = st.text_input("Project Link (optional)", key=f"proj_link_{idx}",
value=proj.get('link', ''),
help="Link to the project repository, demo, or documentation")
if st.button("Remove Project", key=f"remove_proj_{idx}"):
st.session_state.form_data['projects'].pop(idx)
st.rerun()
# Education Section
st.subheader("Education")
if 'education' not in st.session_state.form_data:
st.session_state.form_data['education'] = []
if st.button("Add Education"):
st.session_state.form_data['education'].append({
'school': '',
'degree': '',
'field': '',
'graduation_date': '',
'gpa': '',
'achievements': []
})
for idx, edu in enumerate(st.session_state.form_data['education']):
with st.expander(f"Education {idx + 1}", expanded=True):
col1, col2 = st.columns(2)
with col1:
edu['school'] = st.text_input(
"School/University",
key=f"school_{idx}",
value=edu.get(
'school',
''))
edu['degree'] = st.text_input(
"Degree", key=f"degree_{idx}", value=edu.get(
'degree', ''))
with col2:
edu['field'] = st.text_input(
"Field of Study",
key=f"field_{idx}",
value=edu.get(
'field',
''))
edu['graduation_date'] = st.text_input("Graduation Date", key=f"grad_date_{idx}",
value=edu.get('graduation_date', ''))
edu['gpa'] = st.text_input(
"GPA (optional)",
key=f"gpa_{idx}",
value=edu.get(
'gpa',
''))
# Educational Achievements
st.markdown("##### Achievements & Activities")
edu_achv_text = st.text_area("Enter achievements (one per line)",
key=f"edu_achv_{idx}",
value='\n'.join(
edu.get('achievements', [])),
height=100,
help="List academic achievements, relevant coursework, or activities")
edu['achievements'] = [a.strip()
for a in edu_achv_text.split('\n') if a.strip()]
if st.button("Remove Education", key=f"remove_edu_{idx}"):
st.session_state.form_data['education'].pop(idx)
st.rerun()
# Skills Section
st.subheader("Skills")
if 'skills_categories' not in st.session_state.form_data:
st.session_state.form_data['skills_categories'] = {
'technical': [],
'soft': [],
'languages': [],
'tools': []
}
col1, col2 = st.columns(2)
with col1:
tech_skills = st.text_area("Technical Skills (one per line)",
value='\n'.join(
st.session_state.form_data['skills_categories']['technical']),
height=150,
help="Programming languages, frameworks, databases, etc.")
st.session_state.form_data['skills_categories']['technical'] = [
s.strip() for s in tech_skills.split('\n') if s.strip()]
soft_skills = st.text_area("Soft Skills (one per line)",
value='\n'.join(
st.session_state.form_data['skills_categories']['soft']),
height=150,
help="Leadership, communication, problem-solving, etc.")
st.session_state.form_data['skills_categories']['soft'] = [
s.strip() for s in soft_skills.split('\n') if s.strip()]
with col2:
languages = st.text_area("Languages (one per line)",
value='\n'.join(
st.session_state.form_data['skills_categories']['languages']),
height=150,
help="Programming or human languages with proficiency level")
st.session_state.form_data['skills_categories']['languages'] = [
l.strip() for l in languages.split('\n') if l.strip()]
tools = st.text_area("Tools & Technologies (one per line)",
value='\n'.join(
st.session_state.form_data['skills_categories']['tools']),
height=150,
help="Development tools, software, platforms, etc.")
st.session_state.form_data['skills_categories']['tools'] = [
t.strip() for t in tools.split('\n') if t.strip()]
# Update form data in session state
st.session_state.form_data.update({
'summary': summary
})
# Generate Resume button
if st.button("Generate Resume 📄", type="primary"):
print("Validating form data...")
print(f"Session state form data: {st.session_state.form_data}")
print(f"Email input value: {st.session_state.get('email_input', '')}")
# Get the current values from form
current_name = st.session_state.form_data['personal_info']['full_name'].strip(
)
current_email = st.session_state.email_input if 'email_input' in st.session_state else ''
print(f"Current name: {current_name}")
print(f"Current email: {current_email}")
# Validate required fields
if not current_name:
st.error("⚠️ Please enter your full name.")
return
if not current_email:
st.error("⚠️ Please enter your email address.")
return
# Update email in form data one final time
st.session_state.form_data['personal_info']['email'] = current_email
try:
print("Preparing resume data...")
# Prepare resume data with current form values
resume_data = {
"personal_info": st.session_state.form_data['personal_info'],
"summary": st.session_state.form_data.get('summary', '').strip(),
"experience": st.session_state.form_data.get('experiences', []),
"education": st.session_state.form_data.get('education', []),
"projects": st.session_state.form_data.get('projects', []),
"skills": st.session_state.form_data.get('skills_categories', {
'technical': [],
'soft': [],
'languages': [],
'tools': []
}),
"template": selected_template
}
print(f"Resume data prepared: {resume_data}")
try:
# Generate resume
resume_buffer = self.builder.generate_resume(resume_data)
if resume_buffer:
try:
# Save resume data to database
save_resume_data(resume_data)
# Offer the resume for download
st.success("✅ Resume generated successfully!")
# Show snowflake effect
st.snow()
st.download_button(
label="Download Resume 📥",
data=resume_buffer,
file_name=f"{current_name.replace(' ', '_')}_resume.docx",
mime="application/vnd.openxmlformats-officedocument.wordprocessingml.document",
on_click=lambda: st.balloons()
)
except Exception as db_error:
print(f"Warning: Failed to save to database: {str(db_error)}")
# Still allow download even if database save fails
st.warning(
"⚠️ Resume generated but couldn't be saved to database")
# Show balloons effect
st.balloons()
st.download_button(
label="Download Resume 📥",
data=resume_buffer,
file_name=f"{current_name.replace(' ', '_')}_resume.docx",
mime="application/vnd.openxmlformats-officedocument.wordprocessingml.document",
on_click=lambda: st.balloons()
)
else:
st.error(
"❌ Failed to generate resume. Please try again.")
print("Resume buffer was None")
except Exception as gen_error:
print(f"Error during resume generation: {str(gen_error)}")
print(f"Full traceback: {traceback.format_exc()}")
st.error(f"❌ Error generating resume: {str(gen_error)}")
except Exception as e:
print(f"Error preparing resume data: {str(e)}")
print(f"Full traceback: {traceback.format_exc()}")
st.error(f"❌ Error preparing resume data: {str(e)}")
st.toast("Check out these repositories: [30-Days-Of-Rust](https://github.com/Hunterdii/30-Days-Of-Rust)", icon="ℹ️")
def render_about(self):
"""Render the about page"""
# Apply modern styles
from ui_components import apply_modern_styles
import base64
import os
# Function to load image as base64
def get_image_as_base64(file_path):
try:
with open(file_path, "rb") as image_file:
encoded = base64.b64encode(image_file.read()).decode()
return f"data:image/jpeg;base64,{encoded}"
except:
return None
# Get image path and convert to base64
image_path = os.path.join(
os.path.dirname(__file__),
"assets",
"124852522.jpeg")
image_base64 = get_image_as_base64(image_path)
apply_modern_styles()
# Add Font Awesome icons and custom CSS
st.markdown("""
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css">
<style>
.profile-section, .vision-section, .feature-card {
text-align: center;
padding: 2rem;
background: rgba(45, 45, 45, 0.9);
border-radius: 20px;
margin: 2rem auto;
max-width: 800px;
}
.profile-image {
width: 200px;
height: 200px;
border-radius: 50%;
margin: 0 auto 1.5rem;
display: block;
object-fit: cover;
border: 4px solid #4CAF50;
}
.profile-name {
font-size: 2.5rem;
color: white;
margin-bottom: 0.5rem;
}
.profile-title {
font-size: 1.2rem;
color: #4CAF50;
margin-bottom: 1.5rem;
}
.social-links {
display: flex;
justify-content: center;
gap: 1.5rem;
margin: 2rem 0;
}
.social-link {
font-size: 2rem;
color: #4CAF50;
transition: all 0.3s ease;
padding: 0.5rem;
border-radius: 50%;
background: rgba(76, 175, 80, 0.1);
width: 60px;
height: 60px;
display: flex;
align-items: center;
justify-content: center;
text-decoration: none;
}
.social-link:hover {
transform: translateY(-5px);
background: #4CAF50;
color: white;
box-shadow: 0 5px 15px rgba(76, 175, 80, 0.3);
}
.bio-text {
color: #ddd;
line-height: 1.8;
font-size: 1.1rem;
margin-top: 2rem;
text-align: left;
}
.vision-text {
color: #ddd;
line-height: 1.8;
font-size: 1.1rem;
font-style: italic;
margin: 1.5rem 0;
text-align: left;
}
.vision-icon {
font-size: 2.5rem;
color: #4CAF50;
margin-bottom: 1rem;
}
.vision-title {
font-size: 2rem;
color: white;
margin-bottom: 1rem;
}
.features-grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
gap: 2rem;
margin: 2rem auto;
max-width: 1200px;
}
.feature-card {
padding: 2rem;
margin: 0;
}
.feature-icon {
font-size: 2.5rem;
color: #4CAF50;
margin-bottom: 1rem;
}
.feature-title {
font-size: 1.5rem;
color: white;
margin: 1rem 0;
}
.feature-description {
color: #ddd;
line-height: 1.6;
}
</style>
""", unsafe_allow_html=True)
# Hero Section
st.markdown("""
<div class="hero-section">
<h1 class="hero-title">About Smart Resume AI</h1>
<p class="hero-subtitle">A powerful AI-driven platform for optimizing your resume</p>
</div>
""", unsafe_allow_html=True)
# Profile Section
st.markdown(f"""
<div class="profile-section">
<img src="{image_base64 if image_base64 else 'https://avatars.githubusercontent.com'}"
alt="Parthib karak"
class="profile-image"
onerror="this.onerror=null; this.src='https://avatars.githubusercontent.com';">
<h2 class="profile-name">Parthib karak</h2>
<p class="profile-title">Full Stack Developer & AI/ML Enthusiast</p>
<div class="social-links">
<a href="https://github.com/babaiii07" class="social-link" target="_blank">
<i class="fab fa-github"></i>
</a>
<a href="https://www.linkedin.com/in/parthib-karak-9a0bb1286" class="social-link" target="_blank">
<i class="fab fa-linkedin"></i>
</a>
<a href="mailto:parthibkarak2004@gmail.com" class="social-link" target="_blank">
<i class="fas fa-envelope"></i>
</a>
</div>
<p class="bio-text">
Hello! I'm a passionate Full Stack Developer with expertise in AI and Machine Learning.
I created Smart Resume AI to revolutionize how job seekers approach their career journey.
With my background in both software development and AI, I've designed this platform to
provide intelligent, data-driven insights for resume optimization.
</p>
</div>
""", unsafe_allow_html=True)
# Vision Section
st.markdown("""
<div class="vision-section">
<i class="fas fa-lightbulb vision-icon"></i>
<h2 class="vision-title">Our Vision</h2>
<p class="vision-text">
"Smart Resume AI represents my vision of democratizing career advancement through technology.
By combining cutting-edge AI with intuitive design, this platform empowers job seekers at
every career stage to showcase their true potential and stand out in today's competitive job market."
</p>
</div>
""", unsafe_allow_html=True)
# Features Section
st.markdown("""
<div class="features-grid">
<div class="feature-card">
<i class="fas fa-robot feature-icon"></i>
<h3 class="feature-title">AI-Powered Analysis</h3>
<p class="feature-description">
Advanced AI algorithms provide detailed insights and suggestions to optimize your resume for maximum impact.
</p>
</div>
<div class="feature-card">
<i class="fas fa-chart-line feature-icon"></i>
<h3 class="feature-title">Data-Driven Insights</h3>
<p class="feature-description">
Make informed decisions with our analytics-based recommendations and industry insights.
</p>
</div>
<div class="feature-card">
<i class="fas fa-shield-alt feature-icon"></i>
<h3 class="feature-title">Privacy First</h3>
<p class="feature-description">
Your data security is our priority. We ensure your information is always protected and private.
</p>
</div>
</div>
<div style="text-align: center; margin: 3rem 0;">
<a href="?page=analyzer" class="cta-button">
Start Your Journey
<i class="fas fa-arrow-right" style="margin-left: 10px;"></i>
</a>
</div>
""", unsafe_allow_html=True)
st.toast("Check out these repositories: [Iriswise](https://github.com/Hunterdii/Iriswise)", icon="ℹ️")
def render_analyzer(self):
"""Render the resume analyzer page"""
apply_modern_styles()
# Page Header
page_header(
"Resume Analyzer",
"Get instant AI-powered feedback to optimize your resume"
)
# Create tabs for Normal Analyzer and AI Analyzer
analyzer_tabs = st.tabs(["Standard Analyzer", "AI Analyzer"])
with analyzer_tabs[0]:
# Job Role Selection
categories = list(self.job_roles.keys())
selected_category = st.selectbox(
"Job Category", categories, key="standard_category")
roles = list(self.job_roles[selected_category].keys())
selected_role = st.selectbox(
"Specific Role", roles, key="standard_role")
role_info = self.job_roles[selected_category][selected_role]
# Display role information
st.markdown(f"""
<div style='background-color: #1e1e1e; padding: 20px; border-radius: 10px; margin: 10px 0;'>
<h3>{selected_role}</h3>
<p>{role_info['description']}</p>
<h4>Required Skills:</h4>
<p>{', '.join(role_info['required_skills'])}</p>
</div>
""", unsafe_allow_html=True)
# File Upload
uploaded_file = st.file_uploader(
"Upload your resume", type=[
'pdf', 'docx'], key="standard_file")
if not uploaded_file:
# Display empty state with a prominent upload button
st.markdown(
self.render_empty_state(
"fas fa-cloud-upload-alt",
"Upload your resume to get started with standard analysis"
),
unsafe_allow_html=True
)
# Add a prominent upload button
col1, col2, col3 = st.columns([1, 2, 1])
with col2:
st.markdown("""
<style>
.upload-button {
background: linear-gradient(90deg, #4b6cb7, #182848);
color: white;
border: none;
border-radius: 10px;
padding: 15px 25px;
font-size: 18px;
font-weight: bold;
cursor: pointer;
width: 100%;
text-align: center;
margin: 20px 0;
box-shadow: 0 4px 10px rgba(0,0,0,0.2);
transition: all 0.3s ease;
}
.upload-button:hover {
transform: translateY(-3px);
box-shadow: 0 6px 15px rgba(0,0,0,0.3);
}
""", unsafe_allow_html=True)
if uploaded_file:
# Add a prominent analyze button
analyze_standard = st.button("🔍 Analyze My Resume",
type="primary",
use_container_width=True,
key="analyze_standard_button")
if analyze_standard:
with st.spinner("Analyzing your document..."):
# Get file content
text = ""
try:
if uploaded_file.type == "application/pdf":
try:
text = self.analyzer.extract_text_from_pdf(uploaded_file)
except Exception as pdf_error:
st.error(f"PDF extraction failed: {str(pdf_error)}")
st.info("Trying alternative PDF extraction method...")
# Try AI analyzer as backup
try:
text = self.ai_analyzer.extract_text_from_pdf(uploaded_file)
except Exception as backup_error:
st.error(f"All PDF extraction methods failed: {str(backup_error)}")
return
elif uploaded_file.type == "application/vnd.openxmlformats-officedocument.wordprocessingml.document":
try:
text = self.analyzer.extract_text_from_docx(uploaded_file)
except Exception as docx_error:
st.error(f"DOCX extraction failed: {str(docx_error)}")
# Try AI analyzer as backup
try:
text = self.ai_analyzer.extract_text_from_docx(uploaded_file)
except Exception as backup_error:
st.error(f"All DOCX extraction methods failed: {str(backup_error)}")
return
else:
text = uploaded_file.getvalue().decode()
if not text or text.strip() == "":
st.error("Could not extract any text from the uploaded file. Please try a different file.")
return
except Exception as e:
st.error(f"Error reading file: {str(e)}")
return
# Analyze the document
analysis = self.analyzer.analyze_resume({'raw_text': text}, role_info)
# Check if analysis returned an error
if 'error' in analysis:
st.error(analysis['error'])
return
# Show snowflake effect
st.snow()
# Save resume data to database
resume_data = {
'personal_info': {
'name': analysis.get('name', ''),
'email': analysis.get('email', ''),
'phone': analysis.get('phone', ''),
'linkedin': analysis.get('linkedin', ''),
'github': analysis.get('github', ''),
'portfolio': analysis.get('portfolio', '')
},
'summary': analysis.get('summary', ''),
'target_role': selected_role,
'target_category': selected_category,
'education': analysis.get('education', []),
'experience': analysis.get('experience', []),
'projects': analysis.get('projects', []),
'skills': analysis.get('skills', []),
'template': ''
}
# Save to database
try:
resume_id = save_resume_data(resume_data)
# Save analysis data
analysis_data = {
'resume_id': resume_id,
'ats_score': analysis['ats_score'],
'keyword_match_score': analysis['keyword_match']['score'],
'format_score': analysis['format_score'],
'section_score': analysis['section_score'],
'missing_skills': ','.join(analysis['keyword_match']['missing_skills']),
'recommendations': ','.join(analysis['suggestions'])
}
save_analysis_data(resume_id, analysis_data)
st.success("Resume data saved successfully!")
except Exception as e:
st.error(f"Error saving to database: {str(e)}")
print(f"Database error: {e}")
# Show results based on document type
if analysis.get('document_type') != 'resume':
st.error(
f"⚠️ This appears to be a {analysis['document_type']} document, not a resume!"
)
st.warning(
"Please upload a proper resume for ATS analysis.")
return
# Display results in a modern card layout
col1, col2 = st.columns(2)
with col1:
# ATS Score Card with circular progress
st.markdown("""
<div class="feature-card">
<h2>ATS Score</h2>
<div style="position: relative; width: 150px; height: 150px; margin: 0 auto;">
<div style="
position: absolute;
width: 150px;
height: 150px;
border-radius: 50%;
background: conic-gradient(
#4CAF50 0% {score}%,
#2c2c2c {score}% 100%
);
display: flex;
align-items: center;
justify-content: center;
">
<div style="
width: 120px;
height: 120px;
background: #1a1a1a;
border-radius: 50%;
display: flex;
align-items: center;
justify-content: center;
font-size: 24px;
font-weight: bold;
color: {color};
">
{score}
</div>
</div>
</div>
<div style="text-align: center; margin-top: 10px;">
<span style="
font-size: 1.2em;
color: {color};
font-weight: bold;
">
{status}
</span>
</div>
""".format(
score=analysis['ats_score'],
color='#4CAF50' if analysis['ats_score'] >= 80 else '#FFA500' if analysis[
'ats_score'] >= 60 else '#FF4444',
status='Excellent' if analysis['ats_score'] >= 80 else 'Good' if analysis[
'ats_score'] >= 60 else 'Needs Improvement'
), unsafe_allow_html=True)
st.markdown("</div>", unsafe_allow_html=True)
# self.display_analysis_results(analysis_results)
# Skills Match Card
st.markdown("""
<div class="feature-card">
<h2>Skills Match</h2>
""", unsafe_allow_html=True)
st.metric(
"Keyword Match", f"{int(analysis.get('keyword_match', {}).get('score', 0))}%")
if analysis['keyword_match']['missing_skills']:
st.markdown("#### Missing Skills:")
for skill in analysis['keyword_match']['missing_skills']:
st.markdown(f"- {skill}")
st.markdown("</div>", unsafe_allow_html=True)
with col2:
# Format Score Card
st.markdown("""
<div class="feature-card">
<h2>Format Analysis</h2>
""", unsafe_allow_html=True)
st.metric("Format Score",
f"{int(analysis.get('format_score', 0))}%")
st.metric("Section Score",
f"{int(analysis.get('section_score', 0))}%")
st.markdown("</div>", unsafe_allow_html=True)
# Suggestions Card with improved UI
st.markdown("""
<div class="feature-card">
<h2>📋 Resume Improvement Suggestions</h2>
""", unsafe_allow_html=True)
# Contact Section
if analysis.get('contact_suggestions'):
st.markdown("""
<div style='background-color: #1e1e1e; padding: 15px; border-radius: 10px; margin: 10px 0;'>
<h3 style='color: #4CAF50; margin-bottom: 10px;'>📞 Contact Information</h3>
<ul style='list-style-type: none; padding-left: 0;'>
""", unsafe_allow_html=True)
for suggestion in analysis.get(
'contact_suggestions', []):
st.markdown(
f"<li style='margin-bottom: 8px;'>✓ {suggestion}</li>",
unsafe_allow_html=True)
st.markdown(
"</ul></div>", unsafe_allow_html=True)
# Summary Section
if analysis.get('summary_suggestions'):
st.markdown("""
<div style='background-color: #1e1e1e; padding: 15px; border-radius: 10px; margin: 10px 0;'>
<h3 style='color: #4CAF50; margin-bottom: 10px;'>📝 Professional Summary</h3>
<ul style='list-style-type: none; padding-left: 0;'>
""", unsafe_allow_html=True)
for suggestion in analysis.get(
'summary_suggestions', []):
st.markdown(
f"<li style='margin-bottom: 8px;'>✓ {suggestion}</li>",
unsafe_allow_html=True)
st.markdown(
"</ul></div>", unsafe_allow_html=True)
# Skills Section
if analysis.get(
'skills_suggestions') or analysis['keyword_match']['missing_skills']:
st.markdown("""
<div style='background-color: #1e1e1e; padding: 15px; border-radius: 10px; margin: 10px 0;'>
<h3 style='color: #4CAF50; margin-bottom: 10px;'>🎯 Skills</h3>
<ul style='list-style-type: none; padding-left: 0;'>
""", unsafe_allow_html=True)
for suggestion in analysis.get(
'skills_suggestions', []):
st.markdown(
f"<li style='margin-bottom: 8px;'>✓ {suggestion}</li>",
unsafe_allow_html=True)
if analysis['keyword_match']['missing_skills']:
st.markdown(
"<li style='margin-bottom: 8px;'>✓ Consider adding these relevant skills:</li>",
unsafe_allow_html=True)
for skill in analysis['keyword_match']['missing_skills']:
st.markdown(
f"<li style='margin-left: 20px; margin-bottom: 4px;'>• {skill}</li>",
unsafe_allow_html=True)
st.markdown(
"</ul></div>", unsafe_allow_html=True)
# Experience Section
if analysis.get('experience_suggestions'):
st.markdown("""
<div style='background-color: #1e1e1e; padding: 15px; border-radius: 10px; margin: 10px 0;'>
<h3 style='color: #4CAF50; margin-bottom: 10px;'>💼 Work Experience</h3>
<ul style='list-style-type: none; padding-left: 0;'>
""", unsafe_allow_html=True)
for suggestion in analysis.get(
'experience_suggestions', []):
st.markdown(
f"<li style='margin-bottom: 8px;'>✓ {suggestion}</li>",
unsafe_allow_html=True)
st.markdown(
"</ul></div>", unsafe_allow_html=True)
# Education Section
if analysis.get('education_suggestions'):
st.markdown("""
<div style='background-color: #1e1e1e; padding: 15px; border-radius: 10px; margin: 10px 0;'>
<h3 style='color: #4CAF50; margin-bottom: 10px;'>🎓 Education</h3>
<ul style='list-style-type: none; padding-left: 0;'>
""", unsafe_allow_html=True)
for suggestion in analysis.get(
'education_suggestions', []):
st.markdown(
f"<li style='margin-bottom: 8px;'>✓ {suggestion}</li>",
unsafe_allow_html=True)
st.markdown(
"</ul></div>", unsafe_allow_html=True)
# General Formatting Suggestions
if analysis.get('format_suggestions'):
st.markdown("""
<div style='background-color: #1e1e1e; padding: 15px; border-radius: 10px; margin: 10px 0;'>
<h3 style='color: #4CAF50; margin-bottom: 10px;'>📄 Formatting</h3>
<ul style='list-style-type: none; padding-left: 0;'>
""", unsafe_allow_html=True)
for suggestion in analysis.get(
'format_suggestions', []):
st.markdown(
f"<li style='margin-bottom: 8px;'>✓ {suggestion}</li>",
unsafe_allow_html=True)
st.markdown(
"</ul></div>", unsafe_allow_html=True)
st.markdown("</div>", unsafe_allow_html=True)
# Course Recommendations
st.markdown("""
<div class="feature-card">
<h2>📚 Recommended Courses</h2>
""", unsafe_allow_html=True)
# Get courses based on role and category
courses = get_courses_for_role(selected_role)
if not courses:
category = get_category_for_role(selected_role)
courses = COURSES_BY_CATEGORY.get(
category, {}).get(selected_role, [])
# Display courses in a grid
cols = st.columns(2)
for i, course in enumerate(
courses[:6]): # Show top 6 courses
with cols[i % 2]:
st.markdown(f"""
<div style='background-color: #1e1e1e; padding: 15px; border-radius: 10px; margin: 10px 0;'>
<h4>{course[0]}</h4>
<a href='{course[1]}' target='_blank'>View Course</a>
</div>
""", unsafe_allow_html=True)
st.markdown("</div>", unsafe_allow_html=True)
# Learning Resources
st.markdown("""
<div class="feature-card">
<h2>📺 Helpful Videos</h2>
""", unsafe_allow_html=True)
tab1, tab2 = st.tabs(["Resume Tips", "Interview Tips"])
with tab1:
# Resume Videos
for category, videos in RESUME_VIDEOS.items():
st.subheader(category)
cols = st.columns(2)
for i, video in enumerate(videos):
with cols[i % 2]:
st.video(video[1])
with tab2:
# Interview Videos
for category, videos in INTERVIEW_VIDEOS.items():
st.subheader(category)
cols = st.columns(2)
for i, video in enumerate(videos):
with cols[i % 2]:
st.video(video[1])
st.markdown("</div>", unsafe_allow_html=True)
with analyzer_tabs[1]:
st.markdown("""
<div style='background-color: #1e1e1e; padding: 20px; border-radius: 10px; margin: 10px 0;'>
<h3>AI-Powered Resume Analysis</h3>
<p>Get detailed insights from advanced AI models that analyze your resume and provide personalized recommendations.</p>
<p><strong>Upload your resume to get AI-powered analysis and recommendations.</strong></p>
</div>
""", unsafe_allow_html=True)
# AI Model Selection
ai_model = st.selectbox(
"Select AI Model",
["Groq Llama 3.3 70B"],
help="Choose the AI model to analyze your resume"
)
# Add job description input option
use_custom_job_desc = st.checkbox("Use custom job description", value=False,
help="Enable this to provide a specific job description for more targeted analysis")
custom_job_description = ""
if use_custom_job_desc:
custom_job_description = st.text_area(
"Paste the job description here",
height=200,
placeholder="Paste the full job description from the company here for more targeted analysis...",
help="Providing the actual job description will help the AI analyze your resume specifically for this position"
)
st.markdown("""
<div style='background-color: #2e7d32; padding: 15px; border-radius: 10px; margin: 10px 0;'>
<p><i class="fas fa-lightbulb"></i> <strong>Pro Tip:</strong> Including the actual job description significantly improves the accuracy of the analysis and provides more relevant recommendations tailored to the specific position.</p>
</div>
""", unsafe_allow_html=True)
# Add AI Analyzer Stats in an expander
with st.expander("📊 AI Analyzer Statistics", expanded=False):
try:
# Add a reset button for admin users
if st.session_state.get('is_admin', False):
if st.button(
"🔄 Reset AI Analysis Statistics",
type="secondary",
key="reset_ai_stats_button_2"):
from config.database import reset_ai_analysis_stats
result = reset_ai_analysis_stats()
if result["success"]:
st.success(result["message"])
else:
st.error(result["message"])
# Refresh the page to show updated stats
st.experimental_rerun()
# Get detailed AI analysis statistics
from config.database import get_detailed_ai_analysis_stats
ai_stats = get_detailed_ai_analysis_stats()
if ai_stats["total_analyses"] > 0:
# Create a more visually appealing layout
st.markdown("""
<style>
.stats-card {
background: linear-gradient(135deg, #1e3c72, #2a5298);
border-radius: 10px;
padding: 15px;
margin-bottom: 15px;
box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
text-align: center;
}
.stats-value {
font-size: 28px;
font-weight: bold;
color: white;
margin: 10px 0;
}
.stats-label {
font-size: 14px;
color: rgba(255, 255, 255, 0.8);
text-transform: uppercase;
letter-spacing: 1px;
}
.score-card {
background: linear-gradient(135deg, #11998e, #38ef7d);
border-radius: 10px;
padding: 15px;
margin-bottom: 15px;
box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
text-align: center;
}
</style>
""", unsafe_allow_html=True)
col1, col2, col3 = st.columns(3)
with col1:
st.markdown(f"""
<div class="stats-card">
<div class="stats-label">Total AI Analyses</div>
<div class="stats-value">{ai_stats["total_analyses"]}</div>
</div>
""", unsafe_allow_html=True)
with col2:
# Determine color based on score
score_color = "#38ef7d" if ai_stats["average_score"] >= 80 else "#FFEB3B" if ai_stats[
"average_score"] >= 60 else "#FF5252"
st.markdown(f"""
<div class="stats-card" style="background: linear-gradient(135deg, #2c3e50, {score_color});">
<div class="stats-label">Average Resume Score</div>
<div class="stats-value">{ai_stats["average_score"]}/100</div>
</div>
""", unsafe_allow_html=True)
with col3:
# Create a gauge chart for average score
import plotly.graph_objects as go
fig = go.Figure(go.Indicator(
mode="gauge+number",
value=ai_stats["average_score"],
domain={'x': [0, 1], 'y': [0, 1]},
title={
'text': "Score", 'font': {
'size': 14, 'color': 'white'}},
gauge={
'axis': {'range': [0, 100], 'tickwidth': 1, 'tickcolor': "white"},
'bar': {'color': "#38ef7d" if ai_stats["average_score"] >= 80 else "#FFEB3B" if ai_stats["average_score"] >= 60 else "#FF5252"},
'bgcolor': "rgba(0,0,0,0)",
'borderwidth': 2,
'bordercolor': "white",
'steps': [
{'range': [
0, 40], 'color': 'rgba(255, 82, 82, 0.3)'},
{'range': [
40, 70], 'color': 'rgba(255, 235, 59, 0.3)'},
{'range': [
70, 100], 'color': 'rgba(56, 239, 125, 0.3)'}
],
}
))
fig.update_layout(
paper_bgcolor='rgba(0,0,0,0)',
plot_bgcolor='rgba(0,0,0,0)',
font={'color': "white"},
height=150,
margin=dict(l=10, r=10, t=30, b=10)
)
st.plotly_chart(fig, use_container_width=True)
# Display model usage with enhanced visualization
if ai_stats["model_usage"]:
st.markdown("### 🤖 Model Usage")
model_data = pd.DataFrame(ai_stats["model_usage"])
# Create a more colorful pie chart
import plotly.express as px
fig = px.pie(
model_data,
values="count",
names="model",
color_discrete_sequence=px.colors.qualitative.Bold,
hole=0.4
)
fig.update_traces(
textposition='inside',
textinfo='percent+label',
marker=dict(
line=dict(
color='#000000',
width=1.5))
)
fig.update_layout(
margin=dict(l=20, r=20, t=30, b=20),
height=300,
paper_bgcolor='rgba(0,0,0,0)',
plot_bgcolor='rgba(0,0,0,0)',
font=dict(color="#ffffff", size=14),
legend=dict(
orientation="h",
yanchor="bottom",
y=-0.1,
xanchor="center",
x=0.5
),
title={
'text': 'AI Model Distribution',
'y': 0.95,
'x': 0.5,
'xanchor': 'center',
'yanchor': 'top',
'font': {'size': 18, 'color': 'white'}
}
)
st.plotly_chart(fig, use_container_width=True)
# Display top job roles with enhanced visualization
if ai_stats["top_job_roles"]:
st.markdown("### 🎯 Top Job Roles")
roles_data = pd.DataFrame(
ai_stats["top_job_roles"])
# Create a more colorful bar chart
fig = px.bar(
roles_data,
x="role",
y="count",
color="count",
color_continuous_scale=px.colors.sequential.Viridis,
labels={
"role": "Job Role", "count": "Number of Analyses"}
)
fig.update_traces(
marker_line_width=1.5,
marker_line_color="white",
opacity=0.9
)
fig.update_layout(
margin=dict(l=20, r=20, t=50, b=30),
height=350,
paper_bgcolor='rgba(0,0,0,0)',
plot_bgcolor='rgba(0,0,0,0)',
font=dict(color="#ffffff", size=14),
title={
'text': 'Most Analyzed Job Roles',
'y': 0.95,
'x': 0.5,
'xanchor': 'center',
'yanchor': 'top',
'font': {'size': 18, 'color': 'white'}
},
xaxis=dict(
title="",
tickangle=-45,
tickfont=dict(size=12)
),
yaxis=dict(
title="Number of Analyses",
gridcolor="rgba(255, 255, 255, 0.1)"
),
coloraxis_showscale=False
)
st.plotly_chart(fig, use_container_width=True)
# Add a timeline chart for analysis over time (mock
# data for now)
st.markdown("### 📈 Analysis Trend")
st.info(
"This is a conceptual visualization. To implement actual time-based analysis, additional data collection would be needed.")
# Create mock data for timeline
import datetime
import numpy as np
today = datetime.datetime.now()
dates = [
(today -
datetime.timedelta(
days=i)).strftime('%Y-%m-%d') for i in range(7)]
dates.reverse()
# Generate some random data that sums to
# total_analyses
total = ai_stats["total_analyses"]
if total > 7:
values = np.random.dirichlet(
np.ones(7)) * total
values = [round(v) for v in values]
# Adjust to make sure sum equals total
diff = total - sum(values)
values[-1] += diff
else:
values = [0] * 7
for i in range(total):
values[-(i % 7) - 1] += 1
trend_data = pd.DataFrame({
'Date': dates,
'Analyses': values
})
fig = px.line(
trend_data,
x='Date',
y='Analyses',
markers=True,
line_shape='spline',
color_discrete_sequence=["#38ef7d"]
)
fig.update_traces(
line=dict(width=3),
marker=dict(
size=8, line=dict(
width=2, color='white'))
)
fig.update_layout(
margin=dict(l=20, r=20, t=50, b=30),
height=300,
paper_bgcolor='rgba(0,0,0,0)',
plot_bgcolor='rgba(0,0,0,0)',
font=dict(color="#ffffff", size=14),
title={
'text': 'Analysis Activity (Last 7 Days)',
'y': 0.95,
'x': 0.5,
'xanchor': 'center',
'yanchor': 'top',
'font': {'size': 18, 'color': 'white'}
},
xaxis=dict(
title="",
gridcolor="rgba(255, 255, 255, 0.1)"
),
yaxis=dict(
title="Number of Analyses",
gridcolor="rgba(255, 255, 255, 0.1)"
)
)
st.plotly_chart(fig, use_container_width=True)
# Display score distribution if available
if ai_stats["score_distribution"]:
st.markdown("""
<h3 style='text-align: center; margin-bottom: 20px; background: linear-gradient(90deg, #4b6cb7, #182848); padding: 15px; border-radius: 10px; color: white; box-shadow: 0 4px 10px rgba(0,0,0,0.2);'>
📊 Score Distribution Analysis
</h3>
""", unsafe_allow_html=True)
score_data = pd.DataFrame(
ai_stats["score_distribution"])
# Create a more visually appealing bar chart for
# score distribution
fig = px.bar(
score_data,
x="range",
y="count",
color="range",
color_discrete_map={
"0-20": "#FF5252",
"21-40": "#FF7043",
"41-60": "#FFEB3B",
"61-80": "#8BC34A",
"81-100": "#38ef7d"
},
labels={
"range": "Score Range",
"count": "Number of Resumes"},
text="count" # Display count values on bars
)
fig.update_traces(
marker_line_width=2,
marker_line_color="white",
opacity=0.9,
textposition='outside',
textfont=dict(
color="white", size=14, family="Arial, sans-serif"),
hovertemplate="<b>Score Range:</b> %{x}<br><b>Number of Resumes:</b> %{y}<extra></extra>"
)
# Add a gradient background to the chart
fig.update_layout(
margin=dict(l=20, r=20, t=50, b=30),
height=400, # Increase height for better visibility
paper_bgcolor='rgba(0,0,0,0)',
plot_bgcolor='rgba(0,0,0,0)',
font=dict(
color="#ffffff", size=14, family="Arial, sans-serif"),
# title={
# # 'text': 'Resume Score Distribution',
# 'y': 0.95,
# 'x': 0.5,
# 'xanchor': 'center',
# 'yanchor': 'top',
# 'font': {'size': 22, 'color': 'white', 'family': 'Arial, sans-serif', 'weight': 'bold'}
# },
xaxis=dict(
title=dict(
text="Score Range", font=dict(
size=16, color="white")),
categoryorder="array",
categoryarray=[
"0-20", "21-40", "41-60", "61-80", "81-100"],
tickfont=dict(size=14, color="white"),
gridcolor="rgba(255, 255, 255, 0.1)"
),
yaxis=dict(
title=dict(
text="Number of Resumes", font=dict(
size=16, color="white")),
tickfont=dict(size=14, color="white"),
gridcolor="rgba(255, 255, 255, 0.1)",
zeroline=False
),
showlegend=False,
bargap=0.2, # Adjust gap between bars
shapes=[
# Add gradient background
dict(
type="rect",
xref="paper",
yref="paper",
x0=0,
y0=0,
x1=1,
y1=1,
fillcolor="rgba(26, 26, 44, 0.5)",
layer="below",
line_width=0,
)
]
)
# Add annotations for insights
if len(score_data) > 0:
max_count_idx = score_data["count"].idxmax()
max_range = score_data.iloc[max_count_idx]["range"]
max_count = score_data.iloc[max_count_idx]["count"]
fig.add_annotation(
x=0.5,
y=1.12,
xref="paper",
yref="paper",
text=f"Most resumes fall in the {max_range} score range",
showarrow=False,
font=dict(size=14, color="#FFEB3B"),
bgcolor="rgba(0,0,0,0.5)",
bordercolor="#FFEB3B",
borderwidth=1,
borderpad=4,
opacity=0.8
)
# Display the chart in a styled container
st.markdown("""
<div style='background: linear-gradient(135deg, #1e3c72, #2a5298); padding: 20px; border-radius: 15px; margin: 10px 0; box-shadow: 0 5px 15px rgba(0,0,0,0.2);'>
""", unsafe_allow_html=True)
st.plotly_chart(fig, use_container_width=True)
# Add descriptive text below the chart
st.markdown("""
<p style='color: white; text-align: center; font-style: italic; margin-top: 10px;'>
This chart shows the distribution of resume scores across different ranges, helping identify common performance levels.
</p>
</div>
""", unsafe_allow_html=True)
# Display recent analyses if available
if ai_stats["recent_analyses"]:
st.markdown("""
<h3 style='text-align: center; margin-bottom: 20px; background: linear-gradient(90deg, #4b6cb7, #182848); padding: 15px; border-radius: 10px; color: white; box-shadow: 0 4px 10px rgba(0,0,0,0.2);'>
🕒 Recent Resume Analyses
</h3>
""", unsafe_allow_html=True)
# Create a more modern styled table for recent
# analyses
st.markdown("""
<style>
.modern-analyses-table {
width: 100%;
border-collapse: separate;
border-spacing: 0 8px;
margin-bottom: 20px;
font-family: 'Arial', sans-serif;
}
.modern-analyses-table th {
background: linear-gradient(135deg, #1e3c72, #2a5298);
color: white;
padding: 15px;
text-align: left;
font-weight: bold;
font-size: 14px;
text-transform: uppercase;
letter-spacing: 1px;
border-radius: 8px;
}
.modern-analyses-table td {
padding: 15px;
background-color: rgba(30, 30, 30, 0.7);
border-top: 1px solid rgba(255, 255, 255, 0.05);
border-bottom: 1px solid rgba(0, 0, 0, 0.2);
color: white;
}
.modern-analyses-table tr td:first-child {
border-top-left-radius: 8px;
border-bottom-left-radius: 8px;
}
.modern-analyses-table tr td:last-child {
border-top-right-radius: 8px;
border-bottom-right-radius: 8px;
}
.modern-analyses-table tr:hover td {
background-color: rgba(60, 60, 60, 0.7);
transform: translateY(-2px);
transition: all 0.2s ease;
box-shadow: 0 5px 15px rgba(0, 0, 0, 0.1);
}
.model-badge {
display: inline-block;
padding: 6px 12px;
border-radius: 20px;
font-weight: bold;
text-align: center;
font-size: 12px;
letter-spacing: 0.5px;
box-shadow: 0 2px 5px rgba(0, 0, 0, 0.1);
}
.model-gemini {
background: linear-gradient(135deg, #4e54c8, #8f94fb);
color: white;
}
.model-claude {
background: linear-gradient(135deg, #834d9b, #d04ed6);
color: white;
}
.score-pill {
display: inline-block;
padding: 8px 15px;
border-radius: 20px;
font-weight: bold;
text-align: center;
min-width: 70px;
box-shadow: 0 2px 5px rgba(0, 0, 0, 0.1);
}
.score-high {
background: linear-gradient(135deg, #11998e, #38ef7d);
color: white;
}
.score-medium {
background: linear-gradient(135deg, #f2994a, #f2c94c);
color: white;
}
.score-low {
background: linear-gradient(135deg, #cb2d3e, #ef473a);
color: white;
}
.date-badge {
display: inline-block;
padding: 6px 12px;
border-radius: 20px;
background-color: rgba(255, 255, 255, 0.1);
color: #e0e0e0;
font-size: 12px;
}
.role-badge {
display: inline-block;
padding: 6px 12px;
border-radius: 8px;
background-color: rgba(33, 150, 243, 0.2);
color: #90caf9;
font-size: 13px;
max-width: 200px;
white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;
}
</style>
<div style='background: linear-gradient(135deg, #1e3c72, #2a5298); padding: 20px; border-radius: 15px; margin: 10px 0; box-shadow: 0 5px 15px rgba(0,0,0,0.2);'>
<table class="modern-analyses-table">
<tr>
<th>AI Model</th>
<th>Score</th>
<th>Job Role</th>
<th>Date</th>
</tr>
""", unsafe_allow_html=True)
for analysis in ai_stats["recent_analyses"]:
score = analysis["score"]
score_class = "score-high" if score >= 80 else "score-medium" if score >= 60 else "score-low"
# Determine model class
model_name = analysis["model"]
model_class = "model-gemini" if "Gemini" in model_name else "model-claude" if "Claude" in model_name else ""
# Format the date
try:
from datetime import datetime
date_obj = datetime.strptime(
analysis["date"], "%Y-%m-%d %H:%M:%S")
formatted_date = date_obj.strftime(
"%b %d, %Y")
except:
formatted_date = analysis["date"]
st.markdown(f"""
<tr>
<td><div class="model-badge {model_class}">{model_name}</div></td>
<td><div class="score-pill {score_class}">{score}/100</div></td>
<td><div class="role-badge">{analysis["job_role"]}</div></td>
<td><div class="date-badge">{formatted_date}</div></td>
</tr>
""", unsafe_allow_html=True)
st.markdown("""
</table>
<p style='color: white; text-align: center; font-style: italic; margin-top: 15px;'>
These are the most recent resume analyses performed by our AI models.
</p>
</div>
""", unsafe_allow_html=True)
else:
st.info(
"No AI analysis data available yet. Upload and analyze resumes to see statistics here.")
except Exception as e:
st.error(f"Error loading AI analysis statistics: {str(e)}")
# Job Role Selection for AI Analysis
categories = list(self.job_roles.keys())
selected_category = st.selectbox(
"Job Category", categories, key="ai_category")
roles = list(self.job_roles[selected_category].keys())
selected_role = st.selectbox("Specific Role", roles, key="ai_role")
role_info = self.job_roles[selected_category][selected_role]
# Display role information
st.markdown(f"""
<div style='background-color: #1e1e1e; padding: 20px; border-radius: 10px; margin: 10px 0;'>
<h3>{selected_role}</h3>
<p>{role_info['description']}</p>
<h4>Required Skills:</h4>
<p>{', '.join(role_info['required_skills'])}</p>
</div>
""", unsafe_allow_html=True)
# File Upload for AI Analysis
uploaded_file = st.file_uploader(
"Upload your resume", type=[
'pdf', 'docx'], key="ai_file")
if not uploaded_file:
# Display empty state with a prominent upload button
st.markdown(
self.render_empty_state(
"fas fa-robot",
"Upload your resume to get AI-powered analysis and recommendations"
),
unsafe_allow_html=True
)
else:
# Add a prominent analyze button
analyze_ai = st.button("🤖 Analyze with AI",
type="primary",
use_container_width=True,
key="analyze_ai_button")
if analyze_ai:
with st.spinner(f"Analyzing your resume with {ai_model}..."):
# Get file content
text = ""
try:
if uploaded_file.type == "application/pdf":
text = self.analyzer.extract_text_from_pdf(
uploaded_file)
elif uploaded_file.type == "application/vnd.openxmlformats-officedocument.wordprocessingml.document":
text = self.analyzer.extract_text_from_docx(
uploaded_file)
else:
text = uploaded_file.getvalue().decode()
except Exception as e:
st.error(f"Error reading file: {str(e)}")
st.stop()
# Analyze with AI
try:
# Show a loading animation
with st.spinner("🧠 AI is analyzing your resume..."):
progress_bar = st.progress(0)
# Get the selected model
selected_model = "Groq Llama 3.3 70B"
# Update progress
progress_bar.progress(10)
# Extract text from the resume
analyzer = AIResumeAnalyzer()
if uploaded_file.type == "application/pdf":
resume_text = analyzer.extract_text_from_pdf(
uploaded_file)
elif uploaded_file.type == "application/vnd.openxmlformats-officedocument.wordprocessingml.document":
resume_text = analyzer.extract_text_from_docx(
uploaded_file)
else:
# For text files or other formats
resume_text = uploaded_file.getvalue().decode('utf-8')
# Initialize the AI analyzer (moved after text extraction)
progress_bar.progress(30)
# Get the job role
job_role = selected_role if selected_role else "Not specified"
# Update progress
progress_bar.progress(50)
# Analyze the resume with Groq Llama 3.3 70B
if use_custom_job_desc and custom_job_description:
# Use custom job description for analysis
analysis_result = analyzer.analyze_resume_with_gemini(
resume_text, job_role=job_role, job_description=custom_job_description)
# Show that custom job description was used
st.session_state['used_custom_job_desc'] = True
else:
# Use standard role-based analysis
analysis_result = analyzer.analyze_resume_with_gemini(
resume_text, job_role=job_role)
st.session_state['used_custom_job_desc'] = False
# Update progress
progress_bar.progress(80)
# Save the analysis to the database
if analysis_result and "error" not in analysis_result:
# Extract the resume score
resume_score = analysis_result.get(
"resume_score", 0)
# Save to database
save_ai_analysis_data(
None, # No user_id needed
{
"model_used": selected_model,
"resume_score": resume_score,
"job_role": job_role
}
)
# show snowflake effect
st.snow()
# Complete the progress
progress_bar.progress(100)
# Display the analysis result
if analysis_result and "error" not in analysis_result:
st.success("✅ Analysis complete!")
# Extract data from the analysis
full_response = analysis_result.get(
"analysis", "")
resume_score = analysis_result.get(
"resume_score", 0)
ats_score = analysis_result.get(
"ats_score", 0)
model_used = analysis_result.get(
"model_used", selected_model)
# Store the full response in session state for download
st.session_state['full_analysis'] = full_response
# Display the analysis in a nice format
st.markdown("## Full Analysis Report")
# Get current date
from datetime import datetime
current_date = datetime.now().strftime("%B %d, %Y")
# Create a modern styled header for the report
st.markdown(f"""
<div style="background-color: #262730; padding: 20px; border-radius: 10px; margin-bottom: 20px;">
<h2 style="color: #ffffff; margin-bottom: 10px;">AI Resume Analysis Report</h2>
<div style="display: flex; flex-wrap: wrap; gap: 20px;">
<div style="flex: 1; min-width: 200px;">
<p style="color: #ffffff;"><strong>Job Role:</strong> {job_role if job_role else "Not specified"}</p>
<p style="color: #ffffff;"><strong>Analysis Date:</strong> {current_date}</p> </div>
<div style="flex: 1; min-width: 200px;">
<p style="color: #ffffff;"><strong>AI Model:</strong> {model_used}</p>
<p style="color: #ffffff;"><strong>Overall Score:</strong> {resume_score}/100 - {"Excellent" if resume_score >= 80 else "Good" if resume_score >= 60 else "Needs Improvement"}</p>
{f'<p style="color: #4CAF50;"><strong>✓ Custom Job Description Used</strong></p>' if st.session_state.get('used_custom_job_desc', False) else ''}
</div>
""", unsafe_allow_html=True)
# Add gauge charts for scores
import plotly.graph_objects as go
col1, col2 = st.columns(2)
with col1:
# Resume Score Gauge
fig1 = go.Figure(go.Indicator(
mode="gauge+number",
value=resume_score,
domain={'x': [0, 1], 'y': [0, 1]},
title={'text': "Resume Score", 'font': {'size': 16}},
gauge={
'axis': {'range': [0, 100], 'tickwidth': 1},
'bar': {'color': "#4CAF50" if resume_score >= 80 else "#FFA500" if resume_score >= 60 else "#FF4444"},
'bgcolor': "white",
'borderwidth': 2,
'bordercolor': "gray",
'steps': [
{'range': [0, 40], 'color': 'rgba(255, 68, 68, 0.2)'},
{'range': [40, 60], 'color': 'rgba(255, 165, 0, 0.2)'},
{'range': [60, 80], 'color': 'rgba(255, 214, 0, 0.2)'},
{'range': [80, 100], 'color': 'rgba(76, 175, 80, 0.2)'}
],
'threshold': {
'line': {'color': "red", 'width': 4},
'thickness': 0.75,
'value': 60
}
}
))
fig1.update_layout(
height=250,
margin=dict(l=20, r=20, t=50, b=20),
)
st.plotly_chart(fig1, use_container_width=True)
status = "Excellent" if resume_score >= 80 else "Good" if resume_score >= 60 else "Needs Improvement"
st.markdown(f"<div style='text-align: center; font-weight: bold;'>{status}</div>", unsafe_allow_html=True)
with col2:
# ATS Score Gauge
fig2 = go.Figure(go.Indicator(
mode="gauge+number",
value=ats_score,
domain={'x': [0, 1], 'y': [0, 1]},
title={'text': "ATS Optimization Score", 'font': {'size': 16}},
gauge={
'axis': {'range': [0, 100], 'tickwidth': 1},
'bar': {'color': "#4CAF50" if ats_score >= 80 else "#FFA500" if ats_score >= 60 else "#FF4444"},
'bgcolor': "white",
'borderwidth': 2,
'bordercolor': "gray",
'steps': [
{'range': [0, 40], 'color': 'rgba(255, 68, 68, 0.2)'},
{'range': [40, 60], 'color': 'rgba(255, 165, 0, 0.2)'},
{'range': [60, 80], 'color': 'rgba(255, 214, 0, 0.2)'},
{'range': [80, 100], 'color': 'rgba(76, 175, 80, 0.2)'}
],
'threshold': {
'line': {'color': "red", 'width': 4},
'thickness': 0.75,
'value': 60
}
}
))
fig2.update_layout(
height=250,
margin=dict(l=20, r=20, t=50, b=20),
)
st.plotly_chart(fig2, use_container_width=True)
status = "Excellent" if ats_score >= 80 else "Good" if ats_score >= 60 else "Needs Improvement"
st.markdown(f"<div style='text-align: center; font-weight: bold;'>{status}</div>", unsafe_allow_html=True)
# Add Job Description Match Score if custom job description was used
if st.session_state.get('used_custom_job_desc', False) and custom_job_description:
# Extract job match score from analysis result or calculate it
job_match_score = analysis_result.get("job_match_score", 0)
if not job_match_score and "job_match" in analysis_result:
job_match_score = analysis_result["job_match"].get("score", 0)
# If we have a job match score, display it
if job_match_score:
st.markdown("""
<h3 style="background: linear-gradient(90deg, #4d7c0f, #84cc16); color: white; padding: 10px; border-radius: 5px; margin-top: 20px;">
<i class="fas fa-handshake"></i> Job Description Match Analysis
</h3>
""", unsafe_allow_html=True)
col1, col2 = st.columns(2)
with col1:
# Job Match Score Gauge
fig3 = go.Figure(go.Indicator(
mode="gauge+number",
value=job_match_score,
domain={'x': [0, 1], 'y': [0, 1]},
title={'text': "Job Match Score", 'font': {'size': 16}},
gauge={
'axis': {'range': [0, 100], 'tickwidth': 1},
'bar': {'color': "#4CAF50" if job_match_score >= 80 else "#FFA500" if job_match_score >= 60 else "#FF4444"},
'bgcolor': "white",
'borderwidth': 2,
'bordercolor': "gray",
'steps': [
{'range': [0, 40], 'color': 'rgba(255, 68, 68, 0.2)'},
{'range': [40, 60], 'color': 'rgba(255, 165, 0, 0.2)'},
{'range': [60, 80], 'color': 'rgba(255, 214, 0, 0.2)'},
{'range': [80, 100], 'color': 'rgba(76, 175, 80, 0.2)'}
],
'threshold': {
'line': {'color': "red", 'width': 4},
'thickness': 0.75,
'value': 60
}
}
))
fig3.update_layout(
height=250,
margin=dict(l=20, r=20, t=50, b=20),
)
st.plotly_chart(fig3, use_container_width=True)
match_status = "Excellent Match" if job_match_score >= 80 else "Good Match" if job_match_score >= 60 else "Low Match"
st.markdown(f"<div style='text-align: center; font-weight: bold;'>{match_status}</div>", unsafe_allow_html=True)
with col2:
st.markdown("""
<div style="background-color: #262730; padding: 20px; border-radius: 10px; height: 100%;">
<h4 style="color: #ffffff; margin-bottom: 15px;">What This Means</h4>
<p style="color: #ffffff;">This score represents how well your resume matches the specific job description you provided.</p>
<ul style="color: #ffffff; padding-left: 20px;">
<li><strong>80-100:</strong> Excellent match - your resume is highly aligned with this job</li>
<li><strong>60-79:</strong> Good match - your resume matches many requirements</li>
<li><strong>Below 60:</strong> Consider tailoring your resume more specifically to this job</li>
</ul>
</div>
""", unsafe_allow_html=True)
# Format the full response with better styling
formatted_analysis = full_response
# Replace section headers with styled headers
section_styles = {
"## Overall Assessment": """<div class="report-section">
<h3 style="background: linear-gradient(90deg, #1e3a8a, #3b82f6); color: white; padding: 10px; border-radius: 5px;">
<i class="fas fa-chart-line"></i> Overall Assessment
</h3>
<div class="section-content">""",
"## Professional Profile Analysis": """<div class="report-section">
<h3 style="background: linear-gradient(90deg, #047857, #10b981); color: white; padding: 10px; border-radius: 5px;">
<i class="fas fa-user-tie"></i> Professional Profile Analysis
</h3>
<div class="section-content">""",
"## Skills Analysis": """<div class="report-section">
<h3 style="background: linear-gradient(90deg, #4f46e5, #818cf8); color: white; padding: 10px; border-radius: 5px;">
<i class="fas fa-tools"></i> Skills Analysis
</h3>
<div class="section-content">""",
"## Experience Analysis": """<div class="report-section">
<h3 style="background: linear-gradient(90deg, #9f1239, #e11d48); color: white; padding: 10px; border-radius: 5px;">
<i class="fas fa-briefcase"></i> Experience Analysis
</h3>
<div class="section-content">""",
"## Education Analysis": """<div class="report-section">
<h3 style="background: linear-gradient(90deg, #854d0e, #eab308); color: white; padding: 10px; border-radius: 5px;">
<i class="fas fa-graduation-cap"></i> Education Analysis
</h3>
<div class="section-content">""",
"## Key Strengths": """<div class="report-section">
<h3 style="background: linear-gradient(90deg, #166534, #22c55e); color: white; padding: 10px; border-radius: 5px;">
<i class="fas fa-check-circle"></i> Key Strengths
</h3>
<div class="section-content">""",
"## Areas for Improvement": """<div class="report-section">
<h3 style="background: linear-gradient(90deg, #9f1239, #fb7185); color: white; padding: 10px; border-radius: 5px;">
<i class="fas fa-exclamation-circle"></i> Areas for Improvement
</h3>
<div class="section-content">""",
"## ATS Optimization Assessment": """<div class="report-section">
<h3 style="background: linear-gradient(90deg, #0e7490, #06b6d4); color: white; padding: 10px; border-radius: 5px;">
<i class="fas fa-robot"></i> ATS Optimization Assessment
</h3>
<div class="section-content">""",
"## Recommended Courses": """<div class="report-section">
<h3 style="background: linear-gradient(90deg, #5b21b6, #8b5cf6); color: white; padding: 10px; border-radius: 5px;">
<i class="fas fa-book"></i> Recommended Courses
</h3>
<div class="section-content">""",
"## Resume Score": """<div class="report-section">
<h3 style="background: linear-gradient(90deg, #0369a1, #0ea5e9); color: white; padding: 10px; border-radius: 5px;">
<i class="fas fa-star"></i> Resume Score
</h3>
<div class="section-content">""",
"## Role Alignment Analysis": """<div class="report-section">
<h3 style="background: linear-gradient(90deg, #7c2d12, #ea580c); color: white; padding: 10px; border-radius: 5px;">
<i class="fas fa-bullseye"></i> Role Alignment Analysis
</h3>
<div class="section-content">""",
"## Job Match Analysis": """<div class="report-section">
<h3 style="background: linear-gradient(90deg, #4d7c0f, #84cc16); color: white; padding: 10px; border-radius: 5px;">
<i class="fas fa-handshake"></i> Job Match Analysis
</h3>
<div class="section-content">""",
}
# Apply the styling to each section
for section, style in section_styles.items():
if section in formatted_analysis:
formatted_analysis = formatted_analysis.replace(
section, style)
# Add closing div tags
next_section = False
for next_sec in section_styles.keys():
if next_sec != section and next_sec in formatted_analysis.split(style)[1]:
split_text = formatted_analysis.split(style)[1].split(next_sec)
formatted_analysis = formatted_analysis.split(style)[0] + style + split_text[0] + "</div></div>" + next_sec + "".join(split_text[1:])
next_section = True
break
if not next_section:
formatted_analysis = formatted_analysis + "</div></div>"
# Remove any extra closing div tags that might have been added
formatted_analysis = formatted_analysis.replace("</div></div></div></div>", "</div></div>")
# Ensure we don't have any orphaned closing tags at the end
if formatted_analysis.endswith("</div>"):
# Count opening and closing div tags
open_tags = formatted_analysis.count("<div")
close_tags = formatted_analysis.count("</div>")
# If we have more closing than opening tags, remove the extras
if close_tags > open_tags:
excess = close_tags - open_tags
formatted_analysis = formatted_analysis[:-6 * excess]
# Clean up any visible HTML tags that might appear in the text
formatted_analysis = formatted_analysis.replace("</div>", "")
formatted_analysis = formatted_analysis.replace("<div>", "")
formatted_analysis = formatted_analysis.replace("<div>", "<div>") # Ensure proper opening
formatted_analysis = formatted_analysis.replace("</div>", "</div>") # Ensure proper closing
# Add CSS for the report
st.markdown("""
<style>
.report-section {
margin-bottom: 25px;
border: 1px solid #4B4B4B;
border-radius: 8px;
overflow: hidden;
}
.section-content {
padding: 15px;
background-color: #262730;
color: #ffffff;
}
.report-section h3 {
margin-top: 0;
font-weight: 600;
}
.report-section ul {
padding-left: 20px;
}
.report-section p {
color: #ffffff;
margin-bottom: 10px;
}
.report-section li {
color: #ffffff;
margin-bottom: 5px;
}
</style>
""", unsafe_allow_html=True)
# Display the formatted analysis
st.markdown(f"""
<div style="background-color: #262730; padding: 20px; border-radius: 10px; border: 1px solid #4B4B4B; color: #ffffff;">
{formatted_analysis}
</div>
""", unsafe_allow_html=True)
# Create a PDF report
pdf_buffer = self.ai_analyzer.generate_pdf_report(
analysis_result={
"score": resume_score,
"ats_score": ats_score,
"model_used": model_used,
"full_response": full_response,
"strengths": analysis_result.get("strengths", []),
"weaknesses": analysis_result.get("weaknesses", []),
"used_custom_job_desc": st.session_state.get('used_custom_job_desc', False),
"custom_job_description": custom_job_description if st.session_state.get('used_custom_job_desc', False) else ""
},
candidate_name=st.session_state.get(
'candidate_name', 'Candidate'),
job_role=selected_role
)
# PDF download button
if pdf_buffer:
st.download_button(
label="📊 Download PDF Report",
data=pdf_buffer,
file_name=f"resume_analysis_{datetime.now().strftime('%Y%m%d_%H%M')}.pdf",
mime="application/pdf",
use_container_width=True,
on_click=lambda: st.balloons()
)
else:
st.error("PDF generation failed. Please try again later.")
else:
st.error(f"Analysis failed: {analysis_result.get('error', 'Unknown error')}")
except Exception as ai_error:
st.error(f"Error during AI analysis: {str(ai_error)}")
import traceback as tb
st.code(tb.format_exc())
st.toast("Check out these repositories: [Awesome Java](https://github.com/Hunterdii/Awesome-Java)", icon="ℹ️")
def render_home(self):
apply_modern_styles()
# Hero Section
hero_section(
"Smart Resume AI",
"Transform your career with AI-powered resume analysis and building. Get personalized insights and create professional resumes that stand out."
)
# Features Section
st.markdown('<div class="feature-grid">', unsafe_allow_html=True)
feature_card(
"fas fa-robot",
"AI-Powered Analysis",
"Get instant feedback on your resume with advanced AI analysis that identifies strengths and areas for improvement."
)
feature_card(
"fas fa-magic",
"Smart Resume Builder",
"Create professional resumes with our intelligent builder that suggests optimal content and formatting."
)
feature_card(
"fas fa-chart-line",
"Career Insights",
"Access detailed analytics and personalized recommendations to enhance your career prospects."
)
st.markdown('</div>', unsafe_allow_html=True)
st.toast("Check out these repositories: [AI-Nexus(AI/ML)](https://github.com/Hunterdii/AI-Nexus)", icon="ℹ️")
# Call-to-Action with Streamlit navigation
col1, col2, col3 = st.columns([1, 1, 1])
with col2:
if st.button("Get Started", key="get_started_btn",
help="Click to start analyzing your resume",
type="primary",
use_container_width=True):
cleaned_name = "🔍 RESUME ANALYZER".lower().replace(" ", "_").replace("🔍", "").strip()
st.session_state.page = cleaned_name
st.rerun()
def render_job_search(self):
"""Render the job search page"""
render_job_search()
st.toast("Check out these repositories: [GeeksforGeeks-POTD](https://github.com/Hunterdii/GeeksforGeeks-POTD)", icon="ℹ️")
def render_feedback_page(self):
"""Render the feedback page"""
apply_modern_styles()
# Page Header
page_header(
"Feedback & Suggestions",
"Help us improve by sharing your thoughts"
)
# Initialize feedback manager
feedback_manager = FeedbackManager()
# Create tabs for form and stats
form_tab, stats_tab = st.tabs(["Submit Feedback", "Feedback Stats"])
with form_tab:
feedback_manager.render_feedback_form()
with stats_tab:
feedback_manager.render_feedback_stats()
st.toast("Check out these repositories: [TryHackMe Free Rooms](https://github.com/Hunterdii/tryhackme-free-rooms)", icon="ℹ️")
def show_repo_notification(self):
message = """
<div style="background-color: #1e1e1e; border-radius: 10px; border: 1px solid #4b6cb7; padding: 10px; margin: 10px 0; color: white;">
<div style="margin-bottom: 10px;">Check out these other repositories:</div>
<div style="margin-bottom: 5px;"><b>Hacking Resources:</b></div>
<ul style="margin-top: 0; padding-left: 20px;">
<li><a href="https://github.com/Hunterdii/tryhackme-free-rooms" target="_blank" style="color: #4CAF50;">TryHackMe Free Rooms</a></li>
<li><a href="https://github.com/Hunterdii/Awesome-Hacking" target="_blank" style="color: #4CAF50;">Awesome Hacking</a></li>
</ul>
<div style="margin-bottom: 5px;"><b>Programming Languages:</b></div>
<ul style="margin-top: 0; padding-left: 20px;">
<li><a href="https://github.com/Hunterdii/Awesome-Java" target="_blank" style="color: #4CAF50;">Awesome Java</a></li>
<li><a href="https://github.com/Hunterdii/30-Days-Of-Rust" target="_blank" style="color: #4CAF50;">30 Days Of Rust</a></li>
</ul>
<div style="margin-bottom: 5px;"><b>Data Structures & Algorithms:</b></div>
<ul style="margin-top: 0; padding-left: 20px;">
<li><a href="https://github.com/Hunterdii/GeeksforGeeks-POTD" target="_blank" style="color: #4CAF50;">GeeksforGeeks POTD</a></li>
<li><a href="https://github.com/Hunterdii/Leetcode-POTD" target="_blank" style="color: #4CAF50;">Leetcode POTD</a></li>
</ul>
<div style="margin-bottom: 5px;"><b>AI/ML Projects:</b></div>
<ul style="margin-top: 0; padding-left: 20px;">
<li><a href="https://github.com/Hunterdii/AI-Nexus" target="_blank" style="color: #4CAF50;">AI Nexus</a></li>
</ul>
<div style="margin-top: 10px;">If you find this project helpful, please consider ⭐ starring the repo!</div>
</div>
"""
st.sidebar.markdown(message, unsafe_allow_html=True)
def main(self):
"""Main application entry point"""
self.apply_global_styles()
# Admin login/logout in sidebar
with st.sidebar:
st_lottie(self.load_lottie_url("https://assets5.lottiefiles.com/packages/lf20_xyadoh9h.json"), height=200, key="sidebar_animation")
st.title("Smart Resume AI")
st.markdown("---")
# Navigation buttons
for page_name in self.pages.keys():
if st.button(page_name, use_container_width=True):
cleaned_name = page_name.lower().replace(" ", "_").replace("🏠", "").replace("🔍", "").replace("📝", "").replace("📊", "").replace("🎯", "").replace("💬", "").replace("ℹ️", "").strip()
st.session_state.page = cleaned_name
st.rerun()
# Add some space before admin login
st.markdown("<br><br>", unsafe_allow_html=True)
st.markdown("---")
# Admin Login/Logout section at bottom
if st.session_state.get('is_admin', False):
st.success(f"Logged in as: {st.session_state.get('current_admin_email')}")
if st.button("Logout", key="logout_button"):
try:
log_admin_action(st.session_state.get('current_admin_email'), "logout")
st.session_state.is_admin = False
st.session_state.current_admin_email = None
st.success("Logged out successfully!")
st.rerun()
except Exception as e:
st.error(f"Error during logout: {str(e)}")
else:
with st.expander("👤 Admin Login"):
admin_email_input = st.text_input("Email", key="admin_email_input")
admin_password = st.text_input("Password", type="password", key="admin_password_input")
if st.button("Login", key="login_button"):
try:
if verify_admin(admin_email_input, admin_password):
st.session_state.is_admin = True
st.session_state.current_admin_email = admin_email_input
log_admin_action(admin_email_input, "login")
st.success("Logged in successfully!")
st.rerun()
else:
st.error("Invalid credentials")
except Exception as e:
st.error(f"Error during login: {str(e)}")
# Display the repository notification in the sidebar
self.show_repo_notification()
# Force home page on first load
if 'initial_load' not in st.session_state:
st.session_state.initial_load = True
st.session_state.page = 'home'
st.rerun()
# Get current page and render it
current_page = st.session_state.get('page', 'home')
# Create a mapping of cleaned page names to original names
page_mapping = {name.lower().replace(" ", "_").replace("🏠", "").replace("🔍", "").replace("📝", "").replace("📊", "").replace("🎯", "").replace("💬", "").replace("ℹ️", "").strip(): name
for name in self.pages.keys()}
# Render the appropriate page
if current_page in page_mapping:
self.pages[page_mapping[current_page]]()
else:
# Default to home page if invalid page
self.render_home()
# Add footer to every page
self.add_footer()
if __name__ == "__main__":
app = ResumeApp()
app.main() |