RAGNA Studio Backend

⚠️ DISCLAIMER: This project is not intended for production use. It is provided as-is for educational, research, and development purposes only. Use at your own risk.

RAGNA Studio Backend is an open-source AI-powered API backend built with NestJS, featuring Retrieval-Augmented Generation (RAG), Named Entity Recognition (NER), and multi-provider AI integrations. This project provides a robust foundation for building AI applications with document processing, chat interfaces, and intelligent assistants.

🔗 Looking for the frontend? Check out the companion RAGNA Studio Frontend repository for the complete user interface.

🌟 Features

Core Architecture

• NestJS Framework: Efficient, scalable, and high-performance async API endpoints
• Modular Design: Maintainable architecture that scales with your needs
• TypeScript: Full type safety throughout the codebase
• Prisma ORM: Type-safe database interactions with PostgreSQL
• Redis Integration: Caching and session management
• BullMQ: Background job processing for heavy operations
• WebSocket Support: Real-time communication capabilities
• OpenAPI Documentation: Auto-generated API documentation

AI & ML Capabilities

• RAG (Retrieval-Augmented Generation): Advanced document retrieval and generation
• Multi-Provider AI Support: OpenAI, Anthropic, Google, Mistral, and more
• Named Entity Recognition (NER): Extract and process entities from text
• Document Processing: Support for various file formats (PDF, DOCX, etc.)
• Embedding Generation: Vector embeddings for semantic search
• Chat Interfaces: Real-time chat with AI assistants

Security & Performance

• Role-Based Access Control (RBAC): Granular permission management
• JWT Authentication: Secure token-based authentication with rotation
• Session Management: Secure user session handling
• Input Sanitization: Protection against malicious inputs
• CORS Configuration: Cross-origin resource sharing controls
• Rate Limiting: API abuse protection
• Comprehensive Logging: Structured logging with debug traces

Developer Experience

• Clean Architecture: Object-oriented design with dependency injection
• Separation of Concerns: Modular code organization
• TypeScript SDK: Pre-built, type-safe API client
• Code Quality Tools: Prettier, ESLint, and comprehensive testing
• Environment Configuration: Easy setup for different environments
• Docker Support: Containerized development and deployment

🚀 Quick Start

Prerequisites

• Node.js 22+ and npm/yarn
• Docker & Docker Compose (recommended for development)
• PostgreSQL 13+ (if not using Docker)
• Redis 6+ (if not using Docker)
• Minimum 8GB RAM (for AI model operations)

Installation

1. Clone the repository

   git clone https://github.com/hopkins385/ragna-studio-backend.git
   cd ragna-studio-backend

2. Install dependencies

   npm install

3. Environment Setup

   # Copy the example environment file
   cp .env.example .env
   
   # Edit the .env file with your configuration
   nano .env

4. Database Setup

   # Start PostgreSQL and Redis with Docker
   docker-compose up -d postgres redis
   
   # Run database migrations
   npm run migrate
   
   # Seed the database (optional)
   npm run seed:init

5. Start the Development Server

   npm run dev

The API will be available at http://localhost:3000 with auto-generated documentation at http://localhost:3000/api.

Docker Development

For a complete development environment with all services:

# Start all services
docker-compose -f docker-compose.dev.yml up

# Or run in detached mode
docker-compose -f docker-compose.dev.yml up -d

📖 Documentation

• API Documentation: Available at /api when running the server
• Database Schema: Check prisma/schema.prisma for the complete data model
• Environment Variables: See .env.example for all configuration options

🏗️ RAGNA Studio Ecosystem

This backend is part of the complete RAGNA Studio platform:

• RAGNA Studio Backend (this repository) - AI-powered API backend
• RAGNA Studio Frontend - Modern React-based user interface
• RAGNA SDK - TypeScript SDK for easy integration with RAGNA Studio APIs

For the full experience, you'll want to set up both the backend and frontend repositories. The SDK provides a convenient way to integrate RAGNA Studio's AI capabilities into your own applications with type-safe API calls and built-in error handling.

🧪 Testing

# Run unit tests
npm run test

# Run tests in watch mode
npm run test:watch

# Run end-to-end tests
npm run test:e2e

# Generate coverage report
npm run test:cov

🛠️ Development

Project Structure

src/
├── modules/           # Feature modules (auth, chat, documents, etc.)
├── common/           # Shared utilities, guards, decorators
├── config/           # Configuration files
└── filter/           # Exception filters

prisma/
├── schema.prisma     # Database schema
├── migrations/       # Database migrations
└── seed/            # Database seeders

Key Modules

• Auth: User authentication and authorization
• Chat: Real-time chat functionality with AI assistants
• Documents: Document upload, processing, and management
• AI Models: Integration with various AI providers
• Assistants: Configurable AI assistants with tools
• Collections: Document collections and knowledge bases

Scripts

npm run build        # Build the application
npm run dev          # Start development server
npm run start:prod   # Start production server
npm run lint         # Run ESLint
npm run format       # Format code with Prettier
npm run migrate      # Run database migrations
npm run seed:init    # Seed database with initial data

🔧 Configuration

Key environment variables:

# Database
DATABASE_URL="postgresql://user:pass@localhost:5432/ragna"

# Redis
REDIS_URL="redis://localhost:6379"

# JWT
JWT_SECRET="your-secret-key"

# AI Providers
OPENAI_API_KEY="your-openai-key"
ANTHROPIC_API_KEY="your-anthropic-key"
GOOGLE_API_KEY="your-google-key"

# File Storage
AWS_S3_BUCKET="your-s3-bucket"
AWS_ACCESS_KEY_ID="your-access-key"
AWS_SECRET_ACCESS_KEY="your-secret-key"

🤝 Contributing

We welcome contributions! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

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

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

⚠️ Important Notes

• Not Production Ready: This software is provided for educational and development purposes
• API Keys Required: You'll need API keys from AI providers to use AI features
• Resource Intensive: AI operations require significant computational resources
• Data Privacy: Be mindful of data privacy when processing documents and conversations

🙏 Acknowledgments

• Built with NestJS
• Database ORM by Prisma
• AI integrations powered by Vercel AI SDK
• And many other amazing open-source projects