Job Apply Agent

An intelligent automation system that scrapes job listings and automatically applies to positions on your behalf using tailored resumes and cover letters.

Features

• 🤖 Automated Job Applications: Scrapes job boards and applies to matching positions automatically
• 📄 Resume Tailoring: Uses GPT to customize resumes and cover letters for each application
• 🔐 Secure Authentication: JWT-based authentication with AWS Cognito integration
• 💾 MongoDB Integration: Persistent storage for job data, applications, and user preferences
• ⏰ Scheduled Scraping: Background job scheduler for continuous job monitoring
• 📊 Dashboard: Track application history and job statistics
• 🔧 Preference Management: Configure job preferences, location, salary, and skills
• 📤 Resume Upload: Upload and manage resume PDFs

Tech Stack

Backend

• FastAPI - Modern Python web framework
• MongoDB - NoSQL database
• AWS Cognito - Authentication and authorization
• APScheduler - Background job scheduling
• OpenAI API - GPT integration for resume tailoring

Frontend

• Next.js - React framework
• TypeScript - Type-safe development
• Tailwind CSS - Styling
• AWS Cognito - Client-side auth integration

Project Structure

Job_Apply_Agent/
├── backend/
│   ├── app/
│   │   ├── auth/              # Authentication & Cognito
│   │   ├── jobs/              # Job scraping & auto-apply logic
│   │   ├── resume/            # Resume management & tailoring
│   │   ├── user/              # User preferences & dashboard
│   │   ├── storage/           # File upload handling
│   │   ├── db/                # Database configuration
│   │   ├── main.py            # FastAPI app initialization
│   │   └── config.py          # Configuration management
│   ├── requirements.txt       # Python dependencies
│   └── ...
├── frontend/
│   ├── app/
│   │   ├── login/             # Authentication pages
│   │   ├── dashboard/         # Main dashboard
│   │   ├── apply/             # Job application UI
│   │   ├── upload/            # Resume upload
│   │   ├── preferences/       # User preferences
│   │   └── ...
│   ├── components/            # Reusable React components
│   ├── lib/                   # Utilities and API client
│   ├── package.json           # Node dependencies
│   └── ...

Getting Started

Prerequisites

• Python 3.9+
• Node.js 18+
• MongoDB instance (local or Atlas)
• AWS Cognito user pool configured
• OpenAI API key

Backend Setup

1. Clone and navigate to backend

   cd backend
   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   pip install -r requirements.txt

2. Configure environment variables

   cp .env.example .env

   Update .env with your credentials:

   • MONGODB_URI
   • AWS_COGNITO_USER_POOL_ID
   • AWS_COGNITO_CLIENT_ID
   • OPENAI_API_KEY

3. Run the server

   uvicorn app.main:app --reload

   Backend runs on http://localhost:8000 API docs available at http://localhost:8000/docs

Frontend Setup

1. Navigate to frontend

   cd frontend
   npm install

2. Configure environment variables

   cp .env.example .env.local

   Update with your Cognito configuration and backend URL.

3. Run development server

   npm run dev

   Frontend runs on http://localhost:3000

API Endpoints

Authentication

• POST /auth/login - User login
• POST /auth/signup - User registration
• POST /auth/refresh - Refresh JWT token

Jobs

• GET /jobs/scrape - Scrape jobs from configured platforms
• POST /jobs/apply-now - Apply to specific job
• GET /jobs/applications - Get application history
• POST /jobs/preferences - Update job preferences

Resume

• POST /resume/upload - Upload resume PDF
• GET /resume/text - Get extracted resume text
• POST /resume/tailor - Generate tailored version for job

User

• GET /user/dashboard - Get dashboard data
• GET /user/suggestions - Get personalized job suggestions
• POST /user/preferences - Set user preferences

Configuration

Supported Job Boards

Currently integrated:

• Seek (Australian jobs)

Planned:

• LinkedIn
• Workday
• Lever boards
• Indeed

Credential Storage

Sensitive credentials are encrypted and stored in MongoDB. Configure storage in app/services/credentials.py.

Background Tasks

The system uses APScheduler to run automated tasks:

• Periodic job scraping
• Automatic applications based on preferences
• Resume updates

Configure scheduler intervals in app/jobs/auto_apply_scheduler.py.

Development Roadmap

• Frontend dashboard with job tracking
• JWT validation in all endpoints
• PDF resume upload with text extraction
• Continuous background scraping daemon
• Multi-platform job board support
• End-to-end test endpoint
• Email notifications for successful applications

Contributing

1. Create a feature branch (git checkout -b feature/amazing-feature)
2. Commit your changes (git commit -m 'Add amazing feature')
3. Push to the branch (git push origin feature/amazing-feature)
4. Open a Pull Request

License

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

Support

For issues, questions, or suggestions, please open an issue on GitHub.

Disclaimer

This tool is for personal use. Users are responsible for ensuring compliance with job board terms of service when using automated application features.