ATS Resume Tracker 🤖

A Streamlit-based web application that uses Google's Gemini AI to analyze resumes against job descriptions, providing insights for ATS (Applicant Tracking System) optimization.

📋 Description

This application helps job seekers analyze their resumes against specific job descriptions using AI-powered analysis. It provides three types of feedback:

• Resume analysis and alignment with job requirements
• Improvement suggestions for better job matching
• ATS percentage match scoring

✨ Features

• PDF Resume Upload: Support for multi-page PDF resumes
• AI-Powered Analysis: Uses Google's Gemini 1.5 Flash model
• Three Analysis Types:
  • Resume Analysis & Job Alignment
  • Improvement Suggestions
  • ATS Match Score Calculation
• Multi-Page Support: Processes complete resumes across all pages
• User-Friendly Interface: Clean Streamlit web interface

🛠️ Technologies Used

• Python 3.12+
• Streamlit - Web interface
• Google Generative AI (Gemini) - AI analysis
• pdf2image - PDF processing
• Pillow (PIL) - Image processing
• python-dotenv - Environment variable management

📦 Installation

Prerequisites

1. Python 3.12 or higher
2. Poppler (required for pdf2image):
   • macOS: brew install poppler
   • Windows: Download from Poppler for Windows
   • Linux: sudo apt-get install poppler-utils

Setup Steps

1. Clone the repository:

   git clone <repository-url>
   cd ATS-LLM

2. Create and activate virtual environment:

   python -m venv .venv
   
   # On macOS/Linux:
   source .venv/bin/activate
   
   # On Windows:
   .venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables:

   • Create a .env file in the project root
   • Add your Google API key:

     GOOGLE_API_KEY=your_google_api_key_here
     

5. Get Google API Key:

   • Visit Google AI Studio
   • Create a new API key for Gemini
   • Add it to your .env file

🚀 Usage

1. Start the application:

   streamlit run app.py

2. Open your browser and navigate to http://localhost:8501

3. Use the application:

   • Enter the job description in the text area
   • Upload your resume as a PDF file
   • Choose one of the three analysis options:
     • "Tell me about resume" - General analysis
     • "How can I improve my resume?" - Improvement suggestions
     • "ATS percentage match" - Score calculation

📁 Project Structure

ATS-LLM/
├── app.py              # Main Streamlit application
├── requirements.txt    # Python dependencies
├── .env               # Environment variables (create this)
├── .venv/             # Virtual environment
└── README.md          # Project documentation

🔧 Configuration

The application uses the following environment variables:

• GOOGLE_API_KEY: Your Google Generative AI API key

🤝 Contributing

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

📄 License

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

👨‍💻 Author

Situm Mohanty

• Date: August 31, 2025

🐛 Troubleshooting

Common Issues

1. ModuleNotFoundError: No module named 'pdf2image'

   • Ensure Poppler is installed on your system
   • Verify virtual environment is activated
   • Reinstall requirements: pip install -r requirements.txt

2. Google API Error

   • Check your API key is correctly set in .env
   • Ensure API key has Gemini access enabled
   • Verify API quota hasn't been exceeded

3. PDF Processing Error

   • Ensure PDF is not corrupted
   • Check PDF is not password protected
   • Verify Poppler is properly installed

🔮 Future Enhancements

• Support for Word documents (.docx)
• Batch processing of multiple resumes
• Resume template suggestions
• Export analysis results to PDF
• Integration with job boards
• Resume scoring dashboard

📞 Support

If you encounter any issues or have questions, please:

1. Check the troubleshooting section above
2. Create an issue in the repository
3. Contact the maintainer

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Made with ❤️ using Python and AI by Situm Mohanty