🤖 SmartLearn AI

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🧠 Overview

SmartLearn AI is a modern full-stack AI-powered learning assistant that combines:

• ⚡ FastAPI backend
• 💻 React frontend (Vite)
• 🧠 LLMs (Groq - LLaMA 3)
• 🔍 RAG (Retrieval-Augmented Generation)
• 🗄️ PostgreSQL (persistent chat history)

👉 It allows users to chat with AI and ask questions from uploaded PDFs with context-aware responses.

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✨ Key Features

• 💬 Real-time AI Chat (Groq API)
• 📄 PDF Upload + Q&A
• 🔍 Semantic Search (FAISS)
• 🧠 Context-aware answers (RAG pipeline)
• 🗄️ Persistent chat history (PostgreSQL)
• 🧹 Chat deletion & multi-chat support
• ⚡ FastAPI high-performance backend
• 🎨 Clean ChatGPT-like UI

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🌐 Live Demo

Service	URL
Frontend	https://smart-learn-ai-gules.vercel.app
Backend	https://smartlearn-ai-production.up.railway.app

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🏗️ Project Structure

smartlearn/
│
├── smartlearn-frontend/          # React + Vite frontend
│   ├── src/
│   │   ├── App.jsx
│   │   └── components/
│
├── smartlearn-backend/           # FastAPI backend
│   ├── main.py
│   ├── database.py
│   ├── .env                      # secrets (git-ignored, never commit)
│   └── services/
│       ├── llm.py
│       ├── rag.py
│       └── pdf.py
│
├── README.md
└── .gitignore

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⚙️ Tech Stack

💻 Frontend

• React (Vite)
• Axios
• Tailwind (optional)
• Framer Motion

⚙️ Backend

• FastAPI
• Groq API (LLaMA 3)
• Sentence Transformers
• FAISS
• PostgreSQL (SQLAlchemy)

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🚀 Setup Guide

🔹 1. Clone Repo

git clone https://github.com/YOUR_USERNAME/smartlearn.git
cd smartlearn

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🔹 2. Backend Setup

cd smartlearn-backend
pip install -r requirements.txt

Create smartlearn-backend/.env

GROQ_API_KEY=your_groq_api_key_here
DATABASE_URL=your_railway_public_postgresql_url
ENV=development

⚠️ Important: Use the public Railway DB URL, not the internal one. Go to Railway → PostgreSQL service → Variables tab → copy DATABASE_PUBLIC_URL. It should look like: postgresql://postgres:xxxx@monorail.proxy.rlwy.net:PORT/railway The internal URL (postgres.railway.internal) only works inside Railway — not locally.

Run Backend

uvicorn main:app --reload

📍 Runs on http://127.0.0.1:8000

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🔹 3. Frontend Setup

cd smartlearn-frontend
npm install

Run Frontend

npm run dev

📍 Runs on http://localhost:5173

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🌍 How Environment Switching Works

Where	Environment	CORS policy
Local (uvicorn --reload)	development	allows localhost + Vercel
Railway (deployed)	production	allows Vercel only

The backend reads the ENV variable to decide which origins CORS allows:

• development → allows localhost + Vercel
• production → allows Vercel only (no wildcard *)

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📡 API Endpoints

Method	Endpoint	Description
POST	/chat	Send a message, get AI response
GET	/chats	Get all chat sessions
GET	/chat/{chat_id}	Get messages for a specific chat
DELETE	/chat/{chat_id}	Delete a chat session
POST	/upload	Upload PDF for RAG
GET	/	Health check

POST /chat example

{
  "message": "Explain AI",
  "chat_id": "12345"
}

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🧠 How It Works (RAG + DB Flow)

1. 📄 Upload PDF
2. 🔍 Extract text
3. ✂️ Chunking
4. 🧠 Embeddings (Sentence Transformers)
5. 💾 Store in FAISS (in-memory)
6. ❓ User asks question
7. 🔎 Retrieve relevant context
8. 🤖 Generate answer via Groq (LLaMA 3)
9. 🗄️ Save chat in PostgreSQL

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🗄️ Database Schema

CREATE TABLE chats (
  id         SERIAL PRIMARY KEY,
  chat_id    TEXT,
  message    TEXT,
  response   TEXT,
  created_at TIMESTAMP DEFAULT NOW()
);

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⚠️ Important Notes

• 🔒 Never commit .env — add it to .gitignore
• ⚡ FAISS is in-memory — vector index resets on server restart
• 🌐 Use DATABASE_PUBLIC_URL from Railway for local dev, not the internal URL
• 🔐 Keep GROQ_API_KEY and DATABASE_URL in backend only — never frontend

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🔮 Roadmap

• 🔐 Authentication (JWT/OAUth)
• 🧠 Long-term memory
• 📱 Mobile Optimization
• 💾 Persistent FAISS index

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🤝 Contributing

1. Fork the repo
2. Create your branch (git checkout -b feature/your-feature)
3. Commit your changes (git commit -m 'add: your feature')
4. Push to the branch (git push origin feature/your-feature)
5. Open a Pull Request

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👨‍💻 Team SmartLearn

Name	Role
Sanan Malik	Leader
Naveed Ahmed	Developer
Dua Fatima	Developer
Zeshan Sikandar	Developer
Shayan Umer	Developer
Fiza Imran	Developer

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📌 Status

🚧 Actively Developing

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⭐ Support

If you like this project, give it a ⭐ on GitHub!