Resume Application Tracking System with Google Gemini Pro Vision

Overview

This project implements a Resume Application Tracking System (ATS) using Google Gemini Pro Vision. The system processes resumes, extracts key information, and evaluates candidates based on job descriptions using AI-powered analysis.

Features

• Upload resumes (PDF, DOCX, TXT formats)
• Extract and analyze resume content using Google Gemini Pro Vision
• Compare resumes against job descriptions for relevancy scoring
• Provide structured insights such as skills, experience, and education
• Automated ranking of candidates based on job fit
• API support for integration with HR systems

Technologies Used

• Google Gemini Pro Vision (AI-based document processing)
• Python (Backend processing)
• FastAPI / Flask (API implementation)
• LangChain (AI-powered resume analysis)
• PyMuPDF / pdfplumber (PDF text extraction)
• Tesseract OCR (For scanned resumes)
• OpenAI Embeddings (For semantic search and matching)
• Streamlit / ReactJS (Frontend for user interaction)

Installation

Prerequisites

Ensure you have the following installed:

• Python 3.8+
• pip
• Tesseract OCR (for scanned resume support)

Setup

1. Clone the repository:

   git clone https://github.com/Lucky-akash321/Resume-Application-Tracker-System-ATS-using-Gemini-Pro-Vision
   cd resume-ats-gemini

2. Create a virtual environment and activate it:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install dependencies:

   pip install -r requirements.txt

4. Set up Google Gemini Pro Vision API access (update config.py with API keys).

Usage

1. Start the API server:

   python app.py

2. Access the frontend:

   streamlit run frontend.py

3. Upload a resume and job description to analyze candidate fit.

Example API Call

import requests

url = "http://localhost:8000/match"
data = {
    "resume_id": "12345",
    "job_description": "Data Scientist with Python and Machine Learning experience."
}
response = requests.post(url, json=data)
print(response.json())

Future Enhancements

• Multi-resume comparison for bulk hiring
• Advanced NLP-based skill extraction
• Integration with LinkedIn and job portals

License

This project is licensed under the MIT License.