@energetic-ai/embeddings NPM

EnergeticAI Embeddings

EnergeticAI Embeddings is a library for computing sentence embeddings, which are vector representations of sentences that capture their meaning.

Sentence embeddings can be used for semantic search, recommendations, clustering, and more.

It leverages the Universal Sentence Encoder model from Google Research, which is trained on a variety of data sources and outputs 512-dimensional embeddings.

Install

Install this package, along with @energetic-ai/core and model weights (e.g. @energetic-ai/model-embeddings-en):

npm install @energetic-ai/core @energetic-ai/embeddings @energetic-ai/model-embeddings-en

Usage

You can easily call this method to compute embeddings for a list of sentences, and compare distances:

import { initModel, distance } from "@energetic-ai/embeddings";
import { modelSource } from "@energetic-ai/model-embeddings-en";
(async () => {
  const model = await initModel(modelSource);
  const embeddings = await model.embed(["hello", "world"]);
  console.log(distance(embeddings[0], embeddings[1])));
})();