Panacea - AI Job Assistant

A full-stack web application that helps users generate personalized messages for job applications based on their resume and job descriptions.

🌟 Features

• Resume Analysis: Upload your resume once and have it automatically analyzed to extract key information
• Job Description Analysis: Extract company information, technologies, and requirements from job descriptions
• Personalized Messages: Generate custom messages for different platforms:
  • LinkedIn Connection Requests (200 characters)
  • LinkedIn Messages (300 characters)
  • LinkedIn InMail (2000 characters)
  • Short Emails (1000 characters)
  • Detailed Emails (3000 characters)
  • Y Combinator Applications (500 characters)
• Multiple Resume Profiles: Manage different resume profiles for different job types
• Dashboard: View all your resumes and statistics in a clean interface
• User Authentication: Secure login and registration system

🔧 Tech Stack

Backend

• FastAPI: Modern, fast web framework for building APIs with Python
• SQLAlchemy: SQL toolkit and Object-Relational Mapping (ORM)
• PostgreSQL: Relational database for data storage
• Alembic: Database migration tool
• Claude AI: Integration with Anthropic's Claude API for AI-powered analysis and generation
• JWT: Authentication with JSON Web Tokens
• PDF Processing: Extract text from PDF resumes

Frontend

• React: JavaScript library for building user interfaces
• TypeScript: Static typing for improved development experience
• React Router: For client-side routing
• Axios: HTTP client for API requests
• React Hook Form: Form validation and management
• React Dropzone: File upload functionality
• React Toastify: Notification system
• Tailwind CSS: Utility-first CSS framework for styling

DevOps

• Docker: Container-based deployment with Docker Compose
• Nginx: Web server for the frontend
• Environment Variables: Configuration via .env files
• Continuous Deployment: Ready for deployment on platforms like Render

📋 Getting Started

Prerequisites

• Docker and Docker Compose
• Node.js 18+ (for local development)
• Python 3.10+ (for local development)
• Anthropic API Key (for Claude AI integration)

Environment Setup

Create a .env file in the root directory with the following variables:

SECRET_KEY=your_secret_key
ANTHROPIC_API_KEY=your_anthropic_api_key
ANTHROPIC_MODEL=claude-3-sonnet-20240229

Running with Docker

1. Clone the repository:

git clone https://github.com/your-username/job-message-writer.git
cd job-message-writer

2. Build and start the containers:

docker-compose up -d

This will start:

• Frontend: http://localhost
• Backend: http://localhost:8000
• PostgreSQL database

Running Locally for Development

Backend

1. Navigate to the backend directory:

cd job_message_writer/backend

2. Create a virtual environment:

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

3. Install dependencies:

pip install -r requirements.txt

4. Run database migrations:

alembic upgrade head

5. Start the backend server:

uvicorn app.main:app --reload

Frontend

1. Navigate to the frontend directory:

cd job_message_writer/frontend

2. Install dependencies:

npm install

3. Start the development server:

npm run dev

🗄️ Project Structure

job_message_writer/
├── backend/
│   ├── alembic/                # Database migration scripts
│   ├── app/
│   │   ├── api/
│   │   │   ├── endpoints/      # API route handlers
│   │   │   └── api.py          # API router setup
│   │   ├── core/               # Core settings and configuration
│   │   ├── db/                 # Database models and setup
│   │   ├── llm/                # AI integration modules
│   │   ├── schemas/            # Pydantic schemas for validation
│   │   ├── utils/              # Utility functions
│   │   └── main.py             # Application entry point
│   ├── requirements.txt        # Python dependencies
│   └── Dockerfile              # Backend Docker configuration
├── frontend/
│   ├── public/                 # Public assets
│   ├── src/
│   │   ├── api/                # API client functions
│   │   ├── components/         # React components
│   │   │   └── layout/         # Layout components
│   │   ├── context/            # React context providers
│   │   ├── pages/              # Page components
│   │   ├── App.tsx             # Main application component
│   │   └── main.tsx            # Entry point
│   ├── package.json            # JavaScript dependencies
│   └── Dockerfile              # Frontend Docker configuration
├── docker-compose.yml          # Docker Compose configuration
└── README.md                   # Project documentation

🔐 Authentication

The application uses JWT (JSON Web Tokens) for authentication. Tokens are stored in local storage and attached to API requests through an Axios interceptor.

🗃️ Database Schema

• Users: User accounts and authentication data
• Resumes: Resume profiles with extracted information
• JobDescriptions: Stored job descriptions with company analysis
• Messages: Generated application messages

🚀 Deployment

Render Deployment

This application is configured for easy deployment on Render:

1. Create a new Web Service for the backend
2. Set the build command to pip install -r requirements.txt
3. Set the start command to alembic upgrade head && uvicorn app.main:app --host 0.0.0.0 --port $PORT
4. Add environment variables from the .env file
5. Create a new Static Site for the frontend
6. Set the build command to npm install && npm run build
7. Set the publish directory to dist
8. Add the environment variable VITE_API_BASE_URL pointing to your backend URL

📄 License

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

👨‍💻 Contributing

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

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

📧 Contact

Your Name - Shallum Israel Maryapanor