Smart ATS: Resume Analysis System Using Google Gemini Pro

Abstract

Smart ATS is an innovative Applicant Tracking System that leverages Google's Gemini Pro Vision API to analyze resumes and provide tailored recommendations based on job descriptions. The system uses advanced natural language processing and machine learning techniques to enhance resume quality and improve job application success rates.

Introduction

In today's competitive job market, having a resume that effectively passes through Applicant Tracking Systems (ATS) is crucial. Smart ATS addresses this challenge by providing intelligent resume analysis and recommendations through an intuitive web interface.

Technology Stack

• Frontend: Streamlit
• Backend: Python
• AI Model: Google Gemini Pro Vision API
• PDF Processing: PyPDF2
• Environment Management: python-dotenv

Key Features

1. Resume PDF Processing
   • Efficient PDF text extraction using PyPDF2
   • Support for multi-page resume documents
2. Intelligent Analysis
   • Job description matching percentage
   • Missing keywords identification
   • Customized profile summary
   • Industry-specific recommendations

Implementation Details

Environment Setup

from dotenv import load_dotenv
import google.generativeai as genai
import streamlit as st
import PyPDF2 as pdf
import os

load_dotenv()
genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))

PDF Text Extraction

def input_pdf_text(uploaded_file):
    reader = pdf.PdfReader(uploaded_file)
    text = ""
    for page in range(len(reader.pages)):
        page = reader.pages[page]
        text += str(page.extract_text())
    return text

AI Response Generation

def get_gemini_response(input):
    model = genai.GenerativeModel('gemini-pro')
    response = model.generate_content(input)
    return response.text

Prompt Engineering

The system uses a carefully crafted prompt template that instructs the AI to:

• Act as an experienced ATS evaluator
• Focus on tech fields including software engineering and data science
• Provide percentage matching with job descriptions
• Identify missing keywords
• Generate improvement recommendations

User Interface

The application features a clean, user-friendly interface built with Streamlit that includes:

• Job description input area
• PDF resume upload functionality
• Analysis results display
• Interactive submission button

Results Format

The system outputs results in a structured format:

{
    "JD Match": "70%",
    "MissingKeywords": ["Machine Learning", "Cloud Computing", "AI"],
    "Profile Summary": "Detailed analysis and recommendations..."
}

Future Improvements

1. Support for multiple resume formats (DOCX, TXT)
2. Industry-specific scoring algorithms
3. Interactive resume editing suggestions
4. Batch processing capabilities
5. Resume version tracking

Conclusion

Smart ATS demonstrates the potential of AI-powered resume analysis in improving job application outcomes. The system's ability to provide detailed feedback and recommendations makes it a valuable tool for job seekers in the technical field.

App Link: https://huggingface.co/spaces/AbhayBhaskar/Resume-Application-Tracking-System