EconoVision-Server

Overview

EconoVision-Server is a backend service built using Flask. The project fetches financial and economic data from external APIs and integrates machine learning models to predict future trends, such as foreign exchange rates. By analyzing historical patterns and generating predictions, EconoVision aims to provide actionable insights.

Features

• Flask Framework: Lightweight and powerful Python web framework.
• External API Integration: Fetches financial data (e.g., foreign exchange rates) from trusted sources.
• Dynamic Machine Learning Models: Predicts future trends based on historical data.
• Modular Architecture: Clean and maintainable codebase.

Setup

1. Clone the repository:

   git clone https://github.com/WoongyuChoi/EconoVision-Server.git

2. Navigate into the project directory:

   cd EconoVision-Server

3. Create and activate a virtual environment:

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

4. Install dependencies:

   pip install -r requirements.txt

5. Run the server locally:

   python run.py

6. Deploy to Vercel:

   vercel --prod

Usage

The server fetches historical data and uses machine learning algorithms to predict future trends. For example, given a sequence of foreign exchange rates (1300, 1350, 1400), the system might predict future values like 1410 by identifying unique patterns in the data.

Health Check

GET / HTTP/1.1

Response:

{
  "status": "UP"
}

Exchange Rate Prediction

GET /api/exchange-rate?start_date=20240101&end_date=20241231

Response:

{
  "predicted_rate": 1410.50,
  "confidence": 95.0
}

License

This project is licensed under the MIT License.