SmartRAG

An intelligent Retrieval-Augmented Generation system that automatically selects the best strategy for your data.

📸 Product Demo

Intelligent Multi-Strategy Chat

Interactive Knowledge Graph

✨ Features

• Intelligent RAG Routing - Automatically selects GraphRAG, Vector, or Agentic strategy based on your query
• Multi-Database Storage - MongoDB for documents, Neo4j for knowledge graphs
• CSV/JSON Analysis - Automatic schema extraction and entity detection
• Knowledge Graph Visualization - Interactive force-directed graph of your data
• Markdown Chat - Beautifully formatted responses with typing effect
• LLM Powered - Advanced language model integration

🏗️ Architecture

┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐
│    Frontend     │────▶│     Backend     │────▶│   Databases     │
│   (Next.js)     │     │ (Apollo/Express)│     │ MongoDB + Neo4j │
└─────────────────┘     └─────────────────┘     └─────────────────┘
         │                      │
         │                      ▼
         │              ┌─────────────────┐
         └─────────────▶│    LLM API      │
                        └─────────────────┘

📦 Installation

Prerequisites

• Node.js 18+
• MongoDB (local or Atlas)
• Neo4j (optional, for graph features)
• LLM API key

1. Clone the repository

git clone https://github.com/TrixCoder/smartRAG.git
cd smartRAG

2. Install dependencies

# Backend
cd backend
npm install

# Frontend
cd ../frontend
npm install

3. Configure environment

Create backend/.env:

LLM_API_KEY=your_api_key
DATABASE_URL=mongodb://localhost:27017/smartrag
NEO4J_URI=neo4j+s://your-instance.databases.neo4j.io
NEO4J_USER=neo4j
NEO4J_PASSWORD=your_password

4. Start the servers

# Terminal 1 - Backend
cd backend
npm run dev

# Terminal 2 - Frontend
cd frontend
npm run dev

5. Open the app

Visit http://localhost:3000

🚀 Usage

Upload Data

1. Click the upload icon or drag-and-drop files
2. Supported: CSV, JSON, TXT, PDF, images
3. Data is automatically parsed and entities extracted

Ask Questions

"Find relations in my data"
"Summarize the products by category"
"What are the top 5 brands by price?"

View Knowledge Graph

Click "Knowledge Graph" to see:

• Files as nodes
• Extracted entities connected
• Relationships between data points

🛠️ Tech Stack

Layer	Technology
Frontend	Next.js 14, Apollo Client, Framer Motion
Backend	Node.js, Apollo Server, Express
AI	Advanced LLM
Database	MongoDB, Neo4j
Styling	Tailwind CSS, shadcn/ui

📁 Project Structure

smartRAG/
├── frontend/
│   ├── app/              # Next.js pages
│   ├── components/       # React components
│   └── lib/              # Apollo client, utils
├── backend/
│   ├── src/
│   │   ├── db/           # MongoDB models
│   │   ├── graphql/      # Schema & resolvers
│   │   └── services/     # AI, Neo4j, RAG strategies
│   └── .env.example
└── README.md

🔧 RAG Strategies

Strategy	Use Case
GraphRAG	Relational data, entity networks, "how is A related to B"
Advanced	Document summarization, content retrieval
Agentic	Multi-step tasks, "compare X then calculate Y"

📄 License

MIT

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Submit a pull request

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