Ragify.js

A powerful Retrieval-Augmented Generation (RAG) library for JavaScript/TypeScript.

Demo

Watch the Q&A demo in action:

Features

🚀 Easy to Use: Simple API for document ingestion and querying
🔍 Smart Chunking: Intelligent text splitting with context preservation
🤖 Multiple Embedding Providers: Support for OpenAI and more
💾 Vector Store Integration: Built-in support for Qdrant
📦 TypeScript Support: Full type safety and autocompletion
🛠️ CLI Tool: Command-line interface for quick operations

Quick Start


# Install Ragify.js
yarn add ragify-js
 
# Initialize with OpenAI embeddings
const ragify = new Ragify({
  embeddingProvider: createEmbeddingProvider("openai", "your-api-key"),
  collectionName: "my-documents"
});
 
# Ingest documents
await ragify.ingest({
  text: "Your document text here...",
  metadata: { source: "example" }
});
 
# Query documents
const results = await ragify.query("Your query here");

Documentation

Getting Started - Installation and basic usage
Core Concepts - Understanding the fundamentals
Configuration - Customize your setup
API Reference - Detailed API documentation
CLI Guide - Command-line interface usage
Advanced Topics - Advanced features and patterns
Examples - Code examples and use cases
Contributing - How to contribute to Ragify.js

Why Ragify.js?

Ragify.js is designed to make it easy to build RAG applications in JavaScript/TypeScript. It provides:

Simplicity: Clean, intuitive API that just works
Flexibility: Customizable components and configurations
Performance: Optimized for speed and efficiency
Reliability: Production-ready with comprehensive testing
Community: Active development and support