FinSight is a personal finance insights dashboard powered by Machine Learning. It provides users with smart financial analytics, risk forecasting, and subscription management tools to make better financial decisions.
- Dashboard: Get an overview of your financial health, recent transactions, and key metrics.
- Risk Forecast: Benefit from ML-driven predictions for upcoming expenses and budget risk analysis.
- Subscriptions Management: Automatically detect and track recurring subscriptions, allowing you to easily identify and cancel unwanted services.
- Insights & Anomalies: Get notified about unusual spending patterns or anomalies in your transactions.
Frontend
- React + Vite
- Tailwind CSS
Backend
- Python / FastAPI
- SQLite
- Machine Learning models for forecasting and anomaly detection
- Node.js
- Python 3.9+
- Navigate to the
backenddirectory:cd backend - Create and activate a virtual environment:
python -m venv venv # On Windows: .\venv\Scripts\activate # On macOS/Linux: source venv/bin/activate
- Install dependencies:
pip install -r requirements.txt
- Run the FastAPI development server:
python -m uvicorn main:app --reload
- Navigate to the
finsight-frontenddirectory:cd finsight-frontend - Install dependencies:
npm install
- Start the Vite development server:
npm run dev
/finsight-frontend/: Contains the frontend React application, configured with Vite and initialized with routing and Tailwind CSS./backend/: Contains the backend logic written with FastAPI. This directory houses the API routers, SQL database configuration, Machine Learning scripts, and data generation utilities.