AI-Learning-Platform 🤖

A production-grade mini AI-driven learning system built with FastAPI, React, PostgreSQL, and OpenAI API.

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📌 Project Description

This platform allows users to:

• Register and log in
• Choose a category and sub-category to learn
• Send prompts to an AI (OpenAI GPT)
• View AI-generated lessons
• Track learning history
• Admin view to manage all users and prompts

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🛠 Tech Stack

Backend: Python (FastAPI), SQLAlchemy, PostgreSQL, Uvicorn
Frontend: React, TypeScript, MUI
AI: OpenAI GPT-3.5
DevOps: Docker & Docker Compose
Tools: dotenv, Axios, React Router, VSCode

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📂 Project Structure

AI-Learning-Platform/
├── backend/
│   ├── app/
│   │   ├── models/
│   │   ├── routes/
│   │   ├── services/
│   │   ├── schemas/
│   │   └── main.py
│   ├── Dockerfile
│   └── requirements.txt
├── frontend/
│   ├── src/
│   │   ├── pages/
│   │   ├── features/
│   │   ├── components/
│   │   └── api/
│   ├── Dockerfile
│   └── package.json
└── docker-compose.yml

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🚀 Running the Project Locally

📦 Backend Setup

1. Navigate to backend directory:

   cd backend

2. Create virtual environment:

   python -m venv .venv
   source .venv/bin/activate  

3. Install dependencies:

   pip install -r requirements.txt

4. Add .env file:

   OPENAI_API_KEY=your_key_here
   DATABASE_URL=postgresql+asyncpg://postgres:password@db:5432/learning

5. Run backend:

   uvicorn app.main:app --reload

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🌐 Frontend Setup

1. Navigate to frontend:

   cd frontend

2. Install packages:

   npm install

3. Run React app:

   npm run dev

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🐳 With Docker

To start everything (backend + db):

docker-compose up --build

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🔐 Sample .env File

# backend/.env
OPENAI_API_KEY=sk-************************************
DATABASE_URL=postgresql+asyncpg://postgres:password@db:5432/learning

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📌 API Endpoints Overview

• POST /users/register — Register a user
• POST /users/login — Log in a user
• GET /categories/, GET /sub-categories/:name
• POST /prompts/ — Submit prompt and get AI answer
• GET /prompts/user/:id — View user history
• Admin: GET /prompts/, GET /users/, etc.

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✨ Features

• Modular architecture (models/routes/services)
• AI integration via OpenAI API
• Dynamic category + sub-category structure
• Admin dashboard for full user & prompt control
• Full error handling & validation
• Clean UI with Material Design

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📝 Submission Notes

Public repository:
https://github.com/RachelGenauer/AI-Learning-Platform

Built in 2-3 days as part of a technical fullstack assignment.
Focused on clear architecture, modular code, and real-world standards.

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© 2025 Rachel Genauer. All rights reserved.

📥 Clone the Project

You can clone the project and start working locally with the following command:

git clone https://github.com/RachelGenauer/AI-Learning-Platform.git
cd AI-Learning-Platform