ts-local-embeddings

Browser-first local embedding utilities for:

• Loading a local ONNX embedding model with fallbacks
• Embedding documents in-process or via Web Worker
• Storing vectors in IndexedDB with similarity search and MMR

Documentation

Hosted API docs: https://aicacia.github.io/ts-local-embeddings/docs/

Install

pnpm add @aicacia/local-embeddings @huggingface/transformers @langchain/core

Quick start (Web Worker + IndexedDB)

import { IndexedDBVectorStore, WorkerEmbeddings } from '@aicacia/local-embeddings';
import { Document } from '@langchain/core/documents';

const embeddings = new WorkerEmbeddings({
	runtime: {
		modelPath: '/models/'
	}
});

const store = new IndexedDBVectorStore(embeddings);

await store.addDocuments([
	new Document({ pageContent: 'TypeScript is strongly typed JavaScript' }),
	new Document({ pageContent: 'Transformers can run in the browser with ONNX' })
]);

const matches = await store.similaritySearchWithScore('browser embeddings', 3);
console.log(matches);

When finished, terminate worker resources:

embeddings.terminate();

Runtime options

loadEmbeddingRuntime and WorkerEmbeddings runtime options support:

• modelId: model repo id (default: onnx-community/embeddinggemma-300m-ONNX)
• modelFallbacks: preferred dtype / file fallback order
• allowRemoteModels: when false, require local files only
• modelPath: path passed to transformers as cache_dir; in browser apps this is typically a served model base path like '/models/' or '/my-base/models/'

WorkerEmbeddings also supports:

• onProgress: callback fired during embedDocuments batching with processedAfterBatch and totalDocuments values for UI progress indicators.

To enable internal debug logs while diagnosing runtime/model loading issues, set:

(globalThis as { __LOCAL_EMBEDDINGS_DEBUG__?: boolean }).__LOCAL_EMBEDDINGS_DEBUG__ = true;

Example modelFallbacks:

const embeddings = new WorkerEmbeddings({
	runtime: {
		modelFallbacks: [
			{ dtype: 'q4', model_file_name: 'model_no_gather' },
			{ dtype: 'q4' },
			{ dtype: 'fp16' }
		]
	}
});

Architecture

The library now uses deep internal boundary modules while keeping the public API unchanged:

• embeddingPipeline: owns token limit resolution, adaptive batching, tokenizer/model invocation compatibility, and embedding output validation.
• workerChannel: owns worker request ids, pending promise lifecycle, timeout handling, and failure fan-out semantics.
• vectorWritePipeline: owns write-path dedup policy, cache reuse, deterministic guard behavior, and record mapping.
• indexedDbStoreGateway: owns IndexedDB lifecycle/open-upgrade flow, schema checks, and low-level read/write/query operations.
• runtimePolicy + runtimeLoader: separates fallback-selection policy from the Hugging Face runtime adapter.

Local model files

If you run fully local, host model assets under your configured modelPath, typically:

<public-or-static-root>/models/onnx-community/<model-id>/onnx/*

For SvelteKit, files in static/ are served at the app base path.

Development

pnpm install
pnpm build
pnpm lint
pnpm coverage
pnpm github-pages:dev