Personal Finance Coach

An AI-powered personal finance application that helps users manage their finances, analyze spending patterns, and get personalized financial advice.

Features

• Transaction Management: Upload and categorize financial transactions from CSV, Excel, or JSON files
• Financial Analytics: Comprehensive dashboard with spending trends, category breakdowns, and financial metrics
• AI Financial Coach: Chat with an AI assistant for personalized financial advice and recommendations
• Investment Recommendations: Get personalized investment advice based on risk assessment
• Spending Pattern Analysis: Identify unusual transactions and spending trends
• Financial Predictions: Forecast future spending based on historical data

Tech Stack

Backend

• FastAPI: Modern, fast web framework for building APIs
• SQLAlchemy: SQL toolkit and ORM
• PostgreSQL: Primary database
• Redis: Caching and session storage
• OpenAI GPT: AI-powered financial advice
• ChromaDB: Vector database for RAG (Retrieval Augmented Generation)
• Pandas: Data analysis and processing
• Scikit-learn: Machine learning for transaction categorization
• PyTorch: Deep learning for financial predictions

Frontend

• React: User interface library
• Chart.js: Data visualization
• Tailwind CSS: Utility-first CSS framework
• Axios: HTTP client for API calls

Installation

Prerequisites

• Python 3.8+
• Node.js 14+
• PostgreSQL
• Redis

Backend Setup

1. Clone the repository:

git clone <repository-url>
cd personal-finance-coach

2. Create a virtual environment:

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

3. Install dependencies:

pip install -r requirements.txt

4. Set up environment variables:

cp .env.example .env
# Edit .env with your configuration

5. Set up the database:

# Create PostgreSQL database
createdb finance_coach_db

# Run migrations (if using Alembic)
alembic upgrade head

6. Start the backend server:

python main.py

Frontend Setup

1. Navigate to frontend directory:

cd frontend

2. Install dependencies:

npm install

3. Start the development server:

npm start

Configuration

Environment Variables

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

# Database
DATABASE_URL=postgresql://username:password@localhost:5432/finance_coach_db

# Redis
REDIS_URL=redis://localhost:6379

# AI/ML APIs
OPENAI_API_KEY=your_openai_api_key_here
HUGGINGFACE_API_KEY=your_huggingface_api_key_here

# Security
SECRET_KEY=your-super-secret-key-change-this-in-production
ACCESS_TOKEN_EXPIRE_MINUTES=30

# CORS
BACKEND_CORS_ORIGINS=["http://localhost:3000"]

# ChromaDB
CHROMA_DB_PATH=./chroma_db

Usage

1. Upload Transactions: Start by uploading your transaction data in CSV, Excel, or JSON format
2. View Dashboard: Analyze your spending patterns, income, and financial metrics
3. Chat with AI Coach: Ask questions about your finances and get personalized advice
4. Get Investment Recommendations: Receive tailored investment suggestions based on your risk profile

API Documentation

Once the backend is running, visit http://localhost:8000/docs for interactive API documentation.

File Format Support

The application supports the following transaction file formats:

CSV/Excel Columns

• Amount or Transaction Amount: Transaction amount (positive for income, negative for expenses)
• Description or Transaction Description: Transaction description
• Date or Transaction Date: Transaction date
• Category (optional): Transaction category
• Merchant or Payee (optional): Merchant name
• Account or Account Type (optional): Account type

JSON Format

{
  "transactions": [
    {
      "amount": -50.00,
      "description": "Grocery Store",
      "date": "2024-01-15",
      "category": "Groceries",
      "merchant": "Whole Foods"
    }
  ]
}

Contributing

1. Fork the repository
2. Create a 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

License

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

Support

For support, please open an issue on GitHub or contact the development team.