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! 🚀
- 📄 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
- Clone the repository:
git clone https://github.com/marsidmali/talentrank-ai.git
cd talentrank-ai
- Create and activate a virtual environment:
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
- Install dependencies:
pip install -r requirements.txt
- Set up environment variables:
- Copy
.env.example
to.env
- Add your OpenAI API key to the
.env
file
- Copy
- Start the application:
streamlit run src/main.py
- Upload resumes and job description
- Adjust scoring weights (optional)
- Get ranked results and scores
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
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
}
Create a .env
file with:
OPENAI_API_KEY=your_api_key_here
This project is licensed under the MIT License - see the LICENSE file for details.