Mini Investment Platform - Full-Stack Internship Project

This is a full-stack application built for a Winter Internship 2025 program. It simulates a mini investment platform with features for user authentication, product management, investments, and AI-powered insights.

Tech Stack

• Backend: Node.js, Express.js, TypeScript, Prisma
• Frontend: Next.js, React, TypeScript, Tailwind CSS
• Database: MySQL
• DevOps: Docker, Docker Compose
• Testing: Jest, Supertest
• AI: Google Gemini API

Features

• User signup and JWT-based login.
• Admin-only CRUD operations for managing investment products.
• Users can invest their virtual balance into products.
• Dynamic, data-driven dashboard showing user's portfolio, charts, and holdings.
• Secure, server-side integration with the Gemini API for:
  • AI-powered portfolio analysis and suggestions.
  • An interactive chatbot to explain financial terms.
  • On-demand analysis of market tickers.
• Automated API transaction logger.
• Backend Health Check: Includes a /health endpoint for monitoring service status.
• Comprehensive backend test suite with >75% coverage on all testable modules.

Getting Started

Prerequisites

• Docker and Docker Compose must be installed on your machine.
• Node.js (v18+)

Running the Application

1. Clone the repository:

   git clone [https://github.com/MetaFazer/gripinvest_winter_internship_project.git](https://github.com/MetaFazer/gripinvest_winter_internship_project.git)
   cd your-repo-name

2. Set up Environment Variables:

   • In the project root, create a .env file and add your MySQL passwords:

     MYSQL_ROOT_PASSWORD=your_root_password
     DB_USER=db_user
     DB_PASSWORD=db_password
     

   • In the backend folder, create a .env file and add your database URL, JWT secret, Admin ID, and Gemini API Key:

     DATABASE_URL="mysql://db_user:db_password@mysql-db:3306/invest_db"
     JWT_SECRET=your_super_secret
     ADMIN_USER_ID=your_admin_user_id
     GEMINI_API_KEY=your_gemini_api_key
     

   • In the frontend folder, create a .env.local file and add the API URL:

     NEXT_PUBLIC_API_URL=http://localhost:8000/api
     

3. Update Docker Compose (Important): Open your docker-compose.yml file and make sure the environment variables for the mysql-db service match the generic names you used in the .env files:

   services:
     mysql-db:
       # ...
       environment:
         MYSQL_ROOT_PASSWORD: ${MYSQL_ROOT_PASSWORD}
         MYSQL_DATABASE: invest_db # <-- Match this
         MYSQL_USER: db_user      # <-- Match this
         MYSQL_PASSWORD: ${DB_PASSWORD}

4. Run with Docker Compose: From the root of the project, run the following command:

   docker compose up --build

   This will build the images for the backend and frontend, and start all three containers.

5. Access the Application:

   • Frontend: http://localhost:3000
   • Backend API: http://localhost:8000

AI Usage

This project makes extensive use of AI, both in the development process and as a core feature:

• AI-Driven Development: As the project's coding partner, Gemini assisted in writing code, debugging complex issues (like testing environment bugs and styling configuration), and architecting the application. This significantly expedited the development speed.
• In-App AI Features: The application integrates the Google Gemini API to provide users with intelligent insights, including portfolio reviews and a financial chatbot, demonstrating a practical and secure full-stack implementation of generative AI.