RAG (Retrieval-Augmented Generation) framework for Node.js and TypeScript offers a robust solution for building production-ready RAG systems. This framework supports document loading, embedding, vector stores, and semantic search, making it ideal for developers looking to implement advanced retrieval systems. Key features include:

• 📄 Document Loaders - Load text, markdown, and HTML documents.
• 🔢 Embeddings - Generate vector embeddings with pluggable providers.
• 🗄️ Vector Stores - In-memory storage with cosine similarity search.
• 🔍 Semantic retrieval - Find relevant documents by meaning, not just keywords.
• 🎯 Metadata Filtering - Filter results by custom metadata.
• ⚡ Batch Processing - Efficient ingestion with progress tracking.
• 📊 Built-in Examples - Complete RAG workflows ready to run.

Installation is straightforward with npm, and optional dependencies like OpenAI and ChromaDB enhance functionality for production environments. The framework is open source under the MIT license, encouraging community contributions and enhancements.