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📑TalentRank AI: Smart Resume Screening System

Python 3.8+ OpenAI License: MIT

An intelligent resume ranking system powered by GPT-4o that automatically analyzes and ranks resumes based on job descriptions. Save hours of manual screening and find the best candidates faster! 🚀

✨ Features

  • 📄 Smart PDF Parsing: Automatically extracts and structures information from PDF resumes
  • 🎯 Intelligent Matching: Uses GPT-4o to understand and match candidate qualifications with job requirements
  • 💡 Customizable Scoring: Flexible weighting system for different criteria:
    • Skills matching
    • Experience relevance
    • Education alignment
    • Job history analysis

🛠️ Installation

  1. Clone the repository:
git clone https://github.com/marsidmali/talentrank-ai.git
cd talentrank-ai
  1. Create and activate a virtual environment:
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
  1. Install dependencies:
pip install -r requirements.txt
  1. Set up environment variables:
    • Copy .env.example to .env
    • Add your OpenAI API key to the .env file

🚀 Usage

  1. Start the application:
streamlit run src/main.py
  1. Upload resumes and job description
  2. Adjust scoring weights (optional)
  3. Get ranked results and scores

📁 Project Structure

talentrank-ai/
│
├── src/                  # Source code
│   ├── main.py          # Main application
│   ├── resume_parser.py # Resume parsing logic
│   ├── ranker.py       # Ranking algorithm
│   └── utils/          # Utilities
|
├── Resumes/            # Resume storage
├── requirements.txt    # Dependencies
└── README.md          # Documentation

⚙️ Configuration

The system uses the following default weights which can be customized:

DEFAULT_WEIGHTS = {
    "Matching skills weight": 0.3,
    "Missing skills weight": -0.2,
    "Relevant job list weight": 0.2,
    "Relevant degree list weight": 0.1,
    "Years of relevant experience weight": 0.4
}

🔑 Environment Variables

Create a .env file with:

OPENAI_API_KEY=your_api_key_here

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

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