HireSmartAI - AI Resume Shortlister

AI-powered resume screening tool that analyzes resumes against job descriptions and provides instant rankings with match scores.

Features

• Upload multiple PDF resumes (up to 10)
• AI-powered analysis using Groq LLM
• Fit score (0-100) for each candidate
• Skills matching and gap analysis
• Strengths and weaknesses identification
• Ranked results with recommendations
• Downloadable reports
• Bias-free screening (evaluates skills only)

Tech Stack

• Frontend: Streamlit
• AI Engine: Groq API (Free)
• PDF Parser: PyPDF2
• Deployment: Streamlit Cloud

Quick Start

1. Get Groq API Key (Free)

1. Go to console.groq.com
2. Sign up for free
3. Generate an API key
4. Copy the key

2. Configure API Key

Open the .env file and add your API key:

GROQ_API_KEY=gsk_your_actual_api_key_here

Important: Never commit your .env file to git!

3. Run Locally

# Clone or navigate to project folder
cd ai-resume-shortlister

# Install dependencies
pip install -r requirements.txt

# Run the app
streamlit run app.py

4. Open in Browser

The app will open at http://localhost:8501

Deploy to Streamlit Cloud (Free)

Step 1: Push to GitHub

git init
git add .
git commit -m "Initial commit"
git branch -M main
git remote add origin https://github.com/YOUR_USERNAME/ai-resume-shortlister.git
git push -u origin main

Step 2: Deploy

1. Go to share.streamlit.io
2. Sign in with GitHub
3. Click "New app"
4. Select your repository
5. Set main file: app.py
6. Click "Deploy"

Your app will be live in ~2 minutes!

Usage

1. Enter your Groq API key in the sidebar
2. Paste the job description in the left panel
3. Upload PDF resumes in the right panel
4. Click "Analyze Resumes"
5. View ranked results with scores
6. Download the report

How It Works

Upload PDFs → Extract Text → AI Analysis → Ranked Results
     ↓              ↓             ↓              ↓
  PyPDF2       Clean Text      Groq API     Fit Scores

AI Output Format

For each resume, the AI returns:

Field	Description
fit_score	0-100 match score
skills_matched	Skills found in resume
skills_missing	Required skills not found
strengths	Candidate's strong points
weaknesses	Areas of concern
summary	2-3 sentence evaluation
verdict	Strong Fit / Average Fit / Not a Fit
recommendation	Interview recommendation

Project Structure

ai-resume-shortlister/
├── app.py              # Main application
├── requirements.txt    # Dependencies
└── README.md          # Documentation

Privacy & Security

• No data is stored permanently
• All processing happens in-memory
• Resumes are deleted after session
• No login required

Built For

Hackathon 2024 - AI Productivity Tools

License

MIT License