ATS Resume Expert 📝

ATS Resume Expert is a Streamlit-based application designed to analyze resumes against job descriptions using advanced language models. The app helps users identify strengths, improvement areas, and alignment percentage between resumes and job descriptions.

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Features

• PDF to Image Conversion: Converts PDF resumes into images for processing.
• Resume Analysis: Analyzes the resume based on the job description and provides feedback.
• Skill Improvement Suggestions: Suggests specific areas for skill development.
• Match Percentage: Calculates and displays the percentage match between resume and job description.

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Installation Guide

Follow these steps to set up and run the project locally:

1. Clone the Repository

git clone <repository_url>
cd <repository_name>

2. Create a Virtual Environment

Create an isolated environment for the project:

python -m venv venv

3. Activate the Virtual Environment

• On Linux/macOS:

  source venv/bin/activate

• On Windows:

  venv\Scripts\activate

4. Install Dependencies

Install all the required Python packages:

pip install -r requirements.txt

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Dependencies

The application requires the following Python libraries:

• streamlit: For creating the web interface.
• python-dotenv: For managing environment variables securely.
• pdf2image: For converting PDF pages into images.
• base64: For encoding images.
• os: For handling file operations.
• io: For handling input/output streams.
• Pillow: For working with image data.
• groq: For leveraging the Groq API for AI-driven analysis.
• PyMuPDF (fitz): For working with PDF files.

Ensure these dependencies are included in the requirements.txt file.

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Configuration

1. Set Up Environment Variables

Create a .streamlit/secrets.toml file in the project root and add your Groq API Key:

[secrets]
GROQ_API_KEY = "<your_api_key>"

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Running the Application

Once everything is set up, run the application using Streamlit:

streamlit run app.py

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Usage

1. Open the application in your web browser.
2. Select a model from the dropdown list.
3. Input the job role and job description.
4. Upload your resume (in PDF format).
5. Click the desired action button:
   • Tell Me About the Resume: Get a detailed analysis.
   • How Can I Improve My Skills: Receive skill enhancement suggestions.
   • Percentage Match: View the percentage alignment between resume and job description.

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Directory Structure

├── app.py                   # Main application file
├── requirements.txt         # Python dependencies
├── README.md                # Project documentation
├── .streamlit/
│   └── secrets.toml         # Contains API keys and secrets
└── cv_img/                  # Folder for storing converted images

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Contributions

Contributions are welcome! Feel free to fork the repository, make improvements, and create pull requests.

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License

This project is licensed under the MIT License. See the LICENSE file for more details.

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Author

Created by [MagedAlmoliki1].