npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2026 – Pkg Stats / Ryan Hefner

@trovec/embedder-ollama

v2.3.0

Published

Ollama embeddings adapter for Trovec

Readme

@trovec/embedder-ollama

npm

Ollama embeddings adapter for Trovec. Converts text to vector embeddings using a locally running Ollama server.

Zero runtime dependencies — uses Node.js 18+ built-in fetch. No API key required.

Prerequisites

A running Ollama server with an embedding model pulled. See the Ollama setup guide for Docker-based setup, or install Ollama directly:

ollama pull nomic-embed-text

Installation

npm install @trovec/core @trovec/embedder-ollama

Usage

import { create, addWithText, queryByText } from '@trovec/core';
import { createOllamaEmbedder } from '@trovec/embedder-ollama';

const db = await create({
  embedder: createOllamaEmbedder(),
});
// dimensions are automatically resolved from the embedder (768 for the default model)

await addWithText(db, { id: 'doc1', text: 'The cat sat on the mat' });
await addWithText(db, { id: 'doc2', text: 'Dogs love to play fetch' });

const results = await queryByText(db, { text: 'animals sitting', topK: 5 });

Options

createOllamaEmbedder({
  model?: string;        // default: 'nomic-embed-text'
  baseUrl?: string;      // default: 'http://localhost:11434'
  dimensions?: number;   // auto-resolved for known models; required for custom models
})

All options are optional — the defaults work out of the box with a standard Ollama installation. The returned embedder exposes read-only dimensions and model properties. Trovec uses dimensions to auto-configure itself; model is available for logging and diagnostics.

Models

| Model | Dimensions | Size | Notes | |-------|-----------|------|-------| | nomic-embed-text | 768 | ~274 MB | Default, good quality for general use | | mxbai-embed-large | 1024 | ~670 MB | Higher quality, larger model | | all-minilm | 384 | ~45 MB | Lightweight, fast |

Browse more embedding models at ollama.com/search?c=embedding.

For models not in the list above, pass dimensions explicitly:

createOllamaEmbedder({
  model: 'custom-model',
  dimensions: 512,
})

Remote Server

Use baseUrl to point to an Ollama instance on another machine:

createOllamaEmbedder({
  baseUrl: 'http://192.168.1.100:11434',
})

License

MIT