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@lesto/content-embeddings

v0.1.7

Published

PREVIEW (not part of the supported v1 content seam) — build-time embedding generation for semantic search. A fresh build environment downloads the all-MiniLM-L6-v2 model (~25MB via @huggingface/transformers) on first run; cache the model dir in CI. Experi

Readme

@lesto/content-embeddings

Build-time embedding generation for semantic search.

Installation

npm install @lesto/content-embeddings

Quick Start

import { generateEmbeddings, serializeSearchIndex } from "@lesto/content-embeddings";

// Generate embeddings for your content.
// Each entry needs id, slug, and collection; title/content are optional and
// are what gets embedded.
const entries = [
  { id: "post-1", slug: "getting-started", collection: "blog", title: "Getting started with Docks" },
  { id: "post-2", slug: "advanced-patterns", collection: "blog", title: "Advanced patterns and techniques" },
];

const results = await generateEmbeddings(entries);

// Serialize for client-side search
const index = serializeSearchIndex(results);
await Bun.write("public/search-index.json", index);

Features

  • Local model - Uses Hugging Face Transformers
  • Caching - Embeddings are cached for fast rebuilds
  • Binary quantization - 32x compression with minimal quality loss
  • Progressive indexes - Split into tiers for faster loading

Configuration

const results = await generateEmbeddings(entries, {
  maxTextLength: 8192, // Truncate long content before embedding
  snippetLength: 200, // Snippet length stored for result display
  onProgress: ({ current, total, entry }) => {
    console.log(`${current}/${total} processed (${entry})`);
  },
});

Documentation

Full documentation at usedocks.dev

License

MIT