Lightweight TypeScript RAG system with PostgreSQL, OpenAI & Cohere - Built by beavers, for builders 🦫
Client side logger.
Library to generate easy to remember, and sometimes entertaining, human readable ids
A a collection of languages stemmers and stopwords for Lunr Javascript library
The Retrieval-Augmented Generation (RAG) module contains document processing and embedding utilities.
Client side logger.
A rag component for Convex.
A agent component for Convex.
shim console.log to fix emoji space render issues across terminals
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`.
Retrivora AI is a plug-and-play AI engine for RAG chat experiences — generic vector DB + LLM provider, embeddable or standalone.
No description provided.
The official Pinecone TypeScript SDK for building vector search applications with AI/ML.
Extract clean, timestamped YouTube captions, subtitles, transcripts, and video metadata for AI summaries, RAG, search, and slide-ready workflows.
Local RAG MCP Server - Easy-to-setup document search with minimal configuration
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.
Interactive CLI tool for scaffolding modern web projects with production-ready configurations
> LlamaCloud is a new generation of managed parsing, ingestion, and retrieval services, designed to bring production-grade context-augmentation to your LLM and RAG applications.
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QdrantRag vector store and QdrantRagProvider for @mcp-abap-adt/llm-agent.
RAG (Retrieval-Augmented Generation) utilities for Wundr platform - embeddings, chunking, and vector operations