BudgetAI

Team Members:

• Antonio Villarreal (Project Manager)
• Tyler Wong (Scrum Master)
• Robert Kilkenny (Lead Developer)

Advisor:

• Neha Rani

Project Description:

BudgetAI is a web application designed to analyze credit card spending, visualize expenditure trends, and provide AI-driven budgeting recommendations. The application integrates both a frontend (for visualization and user interaction) and a backend (for handling API calls and data storage).

For more detailed information on the project, please refer to the full Project Proposal.

Technologies Used:

• Frontend: React, Vite, JavaScript/TypeScript
• Backend: Python, Flask, MongoDB
• AI Integration: GPT-3.5 Turbo API (via Azure), PandasAI
• Version Control: Git

Getting Started

Prerequisites

To run the full project, you'll need the following applications installed on your machine:

• Node.js or Yarn (for managing frontend dependencies)
• Python 3.0+ (for the backend)
• MongoDB (for database storage)

Make sure to have multiple terminal instances available for running the backend and frontend simultaneously.

Backend Setup

1. Install MongoDB: Ensure that MongoDB is installed and running on your local machine. The backend will connect to it via localhost:27017.

2. Install Dependencies:

   • Run the appropriate setup script based on your operating system:
     • For Windows: install_windows.bat
     • For Unix/Linux: install_unix.sh

3. Set Environment Variables:

   • In the project directory, find the file example.env.
   • Fill in the AZURE_ENDPOINT and AZURE_API_KEY with your credentials for GPT-3.5 Turbo (you can get these credentials from the Azure portal).
   • Rename example.env to .env to activate the environment variables.

4. Run the Backend:

   • Start the Flask server by running the following command:

python app.py

This will start the backend at localhost:8080.

Frontend Setup

Once the backend is running, follow these steps to get the frontend up and running:

1. Navigate to the client directory:

cd ./client

2. Install dependencies:

If you're using npm:

npm install

Or if you're using Yarn:

yarn install

3. Run the Website Locally:

If you're using npm:

npm run dev

Or if you're using Yarn:

yarn run dev

The frontend should now be accessible at http://localhost:5173/BudgetAI/.

Usage

Once both the backend and frontend are running, open the web application in your browser:

• Log in
• Upload your credit card transactions or use a test dataset
• View your spending trends and receive AI-generated budgeting suggestions