🤖 AI-Powered Recruitment Assistant

Streamline your hiring process with automated resume screening and interview scheduling

🎯 What This Does

Transform your recruitment workflow from hours to minutes:

1. Upload Resume → AI extracts and analyzes skills
2. Smart Matching → Compares against job requirements
3. Auto-Decision → Qualifies or rejects with feedback
4. Instant Scheduling → Creates Jitsi meeting + sends email invite

🔥 Key Features

• 📄 Smart Resume Parsing - Extracts skills from PDF resumes using PyPDF2
• 🧠 Intelligent Matching - Compares candidate skills against predefined job requirements
• ⚡ Auto-Scheduling - Generates unique Jitsi meeting links for qualified candidates
• 📧 Email Automation - Sends professional interview invitations via SMTP
• 📊 Skill Gap Analysis - Shows missing skills for rejected candidates
• 🎯 Multi-Role Support - Configurable for different job positions

🏗️ How It Works (Backend Architecture)

graph LR
    A[PDF Upload] --> B[PyPDF2 Parser]
    B --> C[Text Extraction]
    C --> D[Skill Matching Engine]
    D --> E{Meets Requirements?}
    E -->|Yes| F[Jitsi Link Generator]
    E -->|No| G[Skill Gap Report]
    F --> H[SMTP Email Service]
    H --> I[Interview Scheduled ✅]
    G --> J[Rejection with Feedback ❌]

Backend Components:

1. Resume Parser (resume_parser.py)

# Extracts text from PDF and normalizes for matching
def extract_text_from_pdf(pdf_file):
    return PyPDF2.PdfReader(pdf_file).extract_text().lower()

2. Skill Matching Engine (config.py)

# Predefined job requirements with mandatory vs optional skills
JOB_ROLES = {
    "Data Scientist": {
        "mandatory_skills": ["python", "machine learning", "statistics"],
        "preferred_skills": ["sql", "tensorflow", "aws"]
    }
}

3. Interview Scheduler (jitsi_scheduler.py)

# Generates unique meeting rooms and schedules 24h ahead
def create_jitsi_meeting():
    room_id = generate_unique_id()
    return f"https://meet.jit.si/{room_id}"

4. Email Service (email_sender.py)

# SMTP integration with Gmail App Passwords
def send_interview_email(candidate_email, meeting_link, datetime):
    # Professional email template with meeting details

🚀 Quick Start

Prerequisites

• Python 3.8+
• Gmail account with App Password enabled

Installation

# 1. Clone and setup
git clone https://github.com/SimranShaikh20/AI-Powered-Recruitment-Assistant.git
cd AI-Powered-Recruitment-Assistant
pip install -r requirements.txt

# 2. Configure Gmail App Password (required for email sending)
# Visit: https://myaccount.google.com/apppasswords
# Generate 16-character password for "Mail" app

# 3. Run the application
streamlit run app.py

Gmail Setup (One-time)

1. Enable 2-Step Verification: Google Security Settings
2. Generate App Password: App Passwords
   • Select "Mail" → "Other (Custom name)"
   • Copy the 16-character password
3. Use App Password (not your regular Gmail password) in the application

📁 Project Structure

AI-Powered-Recruitment-Assistant/
├── app.py                    # Main Streamlit UI
├── requirements.txt          # Dependencies
├── utils/
│   ├── config.py            # Job roles & skill requirements
│   ├── resume_parser.py     # PDF text extraction
│   ├── jitsi_scheduler.py   # Meeting link generation
│   └── email_sender.py      # SMTP email automation
└── Documentation/
    └── SRS.docx            # System requirements

🔧 Configuration

Add new job roles in utils/config.py:

JOB_ROLES = {
    "Your New Role": {
        "mandatory_skills": ["skill1", "skill2"],
        "preferred_skills": ["skill3", "skill4"],
        "minimum_score": 70  # Percentage threshold
    }
}

🛠️ Tech Stack

• Frontend: Streamlit (Interactive web interface)
• PDF Processing: PyPDF2 (Resume text extraction)
• Video Conferencing: Jitsi Meet (Open-source, no signup required)
• Email Service: SMTP with Gmail (Automated notifications)
• Deployment: Streamlit Cloud (Free hosting)

🎯 Use Cases

• HR Departments: Automate initial resume screening
• Startups: Quick candidate evaluation without complex ATS
• Recruitment Agencies: Bulk resume processing
• Technical Interviews: Skill-based filtering for developers

🤝 Contributing

1. Fork the repository
2. Create feature branch (git checkout -b feature/new-feature)
3. Commit changes (git commit -m 'Add new feature')
4. Push to branch (git push origin feature/new-feature)
5. Open Pull Request

📝 License

This project is open source and available under the MIT License.

👨‍💻 Author

Simran Shaikh - GitHub Profile

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