A simple example showing how to do metadata filtering with RAG using Mastra, OpenAI, and PGVector.
Find and filter RAG-capable MCP servers by meaning or keywords. Local stdio MCP bridge to the RAGMap subregistry (semantic search, filters, explainable scores).
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.
Various implementations of LangChain.js text splitters
Filter object keys and values into a new object
A agent component for Convex.
Filter out reverted commits parsed by conventional-commits-parser.
Personal Data Hub — UnifiedSchema + validators + KG ingest helpers for the data-back-to-the-individual middleware
Plugin utilities for Rolldown
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`.
AskDB Studio: local browser UI for Schema v2 enrichment and sample NL-to-SQL checks.
Retrivora AI is a plug-and-play AI engine for RAG chat experiences — generic vector DB + LLM provider, embeddable or standalone.
Retrieval-Augmented Generation (RAG) and vector search for HazelJS framework
Filter an array of objects to a specific OS
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.
unist utility to create a new tree with nodes that pass a filter
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.
Filter promises concurrently
A through2 to create an Array.prototype.filter analog for streams.
> 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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