A RAG component for Convex.
A a collection of languages stemmers and stopwords for Lunr Javascript library
The Retrieval-Augmented Generation (RAG) module contains document processing and embedding utilities.
A rag component for Convex.
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`.
Retrivora AI is a plug-and-play AI engine for RAG chat experiences — generic vector DB + LLM provider, embeddable or standalone.
Local RAG MCP Server - Easy-to-setup document search with minimal configuration
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.
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.
Declare LLM prompts with TSX
> 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.
Abstract RAG (Retrieval-Augmented Generation) interfaces and shared implementations
<p align="left"> <a href="https://r2r-docs.sciphi.ai"><img src="https://img.shields.io/badge/docs.sciphi.ai-3F16E4" alt="Docs"></a> <a href="https://discord.gg/p6KqD2kjtB"><img src="https://img.shields.io/discord/1120774652915105934?style=social&logo=
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RAG pipeline, document processing, embeddings, and vector stores for ElsiumAI
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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
LanceDB implementation of RAG interfaces for vibe-agent-toolkit
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