Embedding Packages

An easy to slot in component that renders a video embed of popular streaming services.

A tool for semantic chunking of text

Run AI models locally on your machine with node.js bindings for llama.cpp. Enforce a JSON schema on the model output on the generation level

ChromaDB Node for Node-RED

Inspired by LangMem, nodemem-js is a fast, in-memory vector database for Node.js, designed for efficient similarity search of vector embeddings. Perfect for building chat agent memory and semantic retrieval systems.

A NodeJS RAG framework to easily work with LLMs and custom datasets

A NodeJS RAG framework to easily work with LLMs and custom datasets

Smart Chunks are intelligently designed to maximize their value as inputs into embedding models.

[](https://www.npmjs.com/package/llamaflowjs) [](https://www.npmjs.com/package/llamaflowjs) [![NPM Downloads](https://img.shields.io/npm/dm/lla

A NodeJS RAG framework to easily work with LLMs and custom datasets

<p align="center"> <img height="100" width="100" alt="LlamaIndex logo" src="https://ts.llamaindex.ai/square.svg" /> </p> <h1 align="center">LlamaIndex.TS</h1> <h3 align="center"> Data framework for your LLM application. </h3>

MDS and PCA projections in JavaScript

Scraper for oEmbed, Twitter Cards and Open Graph metadata - fast and Promise-based

Easy embeddings for LLMs like gpt-3.5-turbo and gpt-4 using OpenAI's text-embedding-ada-002

Scraper for oEmbed, Twitter Cards and Open Graph metadata - fast and Promise-based

Build AI applications, chatbots, and agents with JavaScript and TypeScript.

🧠 powerful JavaScript library that leverages advanced AI embeddings to perform zero-shot text classification. Whether you're dealing with unlabelled data or seeking to classify text against dynamic and user-defined labels, this library provides a seamles

NodeJS library that semantically chunks text and matches it against a user query using cosine similarity for precise and relevant text retrieval

A NodeJS framework to easily work with LLMs and custom datasets

Various tools for maintaining combinatorial embeddings of network graphs.