CareerMatch AI 🎯

From Resume to Results: How Google Gemini Powers Intelligent Career Matching

An intelligent career matching platform that helps job seekers analyze their resume against job postings and get personalized job search recommendations using AI.

Features

• Resume Analysis

  • Upload PDF resumes or paste resume text
  • Text extraction and processing from PDF files
  • Smart matching with job descriptions

• Job Matching

  • Calculate similarity scores between resumes and job postings
  • Analyze resume-job matches using Gemini Pro AI
  • Get detailed analysis of matching skills and missing requirements
  • Receive suggestions for resume improvement

• Job Search Assistance

  • Get AI-powered job search recommendations based on your resume
  • Find relevant job boards and active listings
  • Receive suggested search terms
  • Discover companies that might be hiring
  • Get industry insights for your skills in Australia

• Cover Letter Generation

  • Generate customized cover letters using AI
  • Based on your resume and target job posting

Project Structure

job-seeker-assistant/
├── src/
│   ├── app.py              # Main application entry point
│   ├── config.py           # Application configuration
│   ├── job_analyzer.py     # Job analysis functionality
│   ├── job_searcher.py     # Job search functionality
│   ├── text_processor.py   # Text processing utilities
│   └── ui.py               # Streamlit UI components
├── requirements.txt        # Python dependencies
├── Pipfile                 # Pipenv dependencies
└── README.md               # This file

Prerequisites

• Python 3.11+
• Google Cloud Project with following APIs enabled:
  • Vertex AI API
  • Gemini API

Running CareerMatch AI locally

1. Clone the repository:

git clone <repository-url>
cd careermatch-ai

2. Install dependencies with either Pipenv or pip:

# Using Pipenv
pipenv install

# OR using pip
pip install -r requirements.txt

3. Set up Google Cloud Credentials

• Run gcloud init to authorize gcloud and other SDK tools to access Google Cloud using your user account credentials.

• Run gcloud auth application-default login to obtain access credentials for your user account via a web-based authorization flow. When this command completes successfully, it sets the active account in the current configuration to the account specified. If no configuration exists, it creates a configuration named default.

4. Start the application:

export GOOGLE_CLOUD_PROJECT=$(gcloud config get-value project) && pipenv run streamlit run src/app.py

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

6. Follow the on-screen instructions:

   • Upload your resume or paste resume text
   • Enter a job posting URL for specific job analysis (optional)
   • Click "Analyze" to get results
   • Optionally generate a cover letter for the job

Technology Stack

• Frontend: Streamlit
• AI/ML:
  • Google Vertex AI
  • Gemini Pro for analysis and generation
  • Google's search capabilities for job recommendations
• Additional Libraries:
  • PyPDF2 for PDF processing
  • BeautifulSoup4 for web scraping
  • Streamlit for UI components
  • Functions Framework for serverless functions

Security & Privacy

• Resume data is processed securely and not stored permanently
• Uses Google Cloud's secure AI infrastructure
• All data processing happens within the session
• No personally identifiable information is stored

Disclaimer

This tool uses AI to analyze resumes and job postings. Results are suggestions only and not guaranteed. Your data is processed securely but not stored. Always review AI-generated content before use in real applications.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Deploy on Cloud Run

If button goes to Cloud Shell Quota issue

Run the following on your Google Cloud Shell

cloudshell_open --repo_url "https://github.com/boltdynamics/careermatch-ai.git" --git_branch "main" --page "shell" --force_new_clone