Production-ready RAG (Retrieval-Augmented Generation) for JavaScript & React - Built on official Ollama & LM Studio SDKs with Hybrid Search, Reranking, Query Transformation, Caching, Conversation Management & Evaluation
A a collection of languages stemmers and stopwords for Lunr Javascript library
The Retrieval-Augmented Generation (RAG) module contains document processing and embedding utilities.
Local RAG MCP Server - Easy-to-setup document search with minimal configuration
A rag component for Convex.
RAG (Retrieval-Augmented Generation) utilities for Wundr platform - embeddings, chunking, and vector operations
Offline HTTP RAG (Retrieval-Augmented Generation) server for the Red Sift Design System — returns ranked, scored documentation chunks for any LLM/agent to consume.
A agent component for Convex.
Phase 2 of the catalog plane. Adds vector embeddings, AI-agent access patterns, and the MCP server scaffolding on top of the Phase 1 foundation in `@voyantjs/catalog`.
Project-local RAG memory MCP server — knowledge graph + multilingual vector + FTS5 in a single SQLite file. Per-project isolation, 30 MCP tools, codepoint-safe chunking (Korean/CJK/emoji).
MCP server that connects AI agents to a configurable RAG Pixels HTTP backend
Retrivora AI is a plug-and-play AI engine for RAG chat experiences — generic vector DB + LLM provider, embeddable or standalone.
Extract clean, timestamped YouTube captions, subtitles, transcripts, and video metadata for AI summaries, RAG, search, and slide-ready workflows.
The official Pinecone TypeScript SDK for building vector search applications with AI/ML.
The official TypeScript library for the Llama Cloud API
Simple RAG Chat using Upstash
SAP AI Provider for Vercel AI SDK (powered by @sap-ai-sdk/orchestration and @sap-ai-sdk/foundation-models)
A TypeScript CLI tool for local RAG indexing and querying
RAG Chat Bot Web Component SDK
RAG block for 23blocks SDK - vector search, document processing, image search, product identification
A JavaScript library for Retrieval-Augmented Generation (RAG) within the QVAC ecosystem. Build powerful, context-aware AI applications with seamless document ingestion, vector search, and LLM integration.
Local RAG MCP Server - Enhanced with hybrid search, memory management, and code file support (fork of shinpr/mcp-local-rag)
Plug-and-play retrieval-augmented generation for AgentsKit.
Official TypeScript/JavaScript SDK for CortexDB - Multi-modal RAG Platform with advanced document processing