# lunr-languages
> A a collection of languages stemmers and stopwords for Lunr Javascript library
Latest version **1.22.0** (published 2026-09-15) · MPL-1.1 license · 0 weekly downloads
## Install
```sh
npm install lunr-languages
pnpm add lunr-languages
yarn add lunr-languages
bun add lunr-languages
```
## Health
**Score 70/100 (B)** — status: active.
Positive: has types; esm support; no vulnerabilities; recently updated; high maintenance score; high quality score.
Warnings: low downloads.
## Facts
| | |
|---|---|
| Version | 1.22.0 |
| Published | 2026-09-15 |
| First published | 2014-07-27 |
| Weekly downloads | 0 |
| License | MPL-1.1 |
| TypeScript types | bundled |
| Module format | ESM + CommonJS |
| Dependencies | 0 |
| Unpacked size | 1.3 MB |
| Known vulnerabilities | 0 |
| Install scripts | no |
| GitHub stars | 458 |
| Author | Mihai Valentin |
| Maintainers | mihaivalentin |
## Links
- npm: https://www.npmjs.com/package/lunr-languages
- Repository: https://github.com/MihaiValentin/lunr-languages
- Homepage: https://github.com/MihaiValentin/lunr-languages#readme
- Issues: https://github.com/MihaiValentin/lunr-languages/issues
- npm.io page: https://npm.io/package/lunr-languages
## Recent versions
- 1.22.0 (latest) — 2026-09-15
- 1.21.0 — 2026-08-09
- 1.20.0 — 2026-05-10
- 1.19.0 — 2026-05-10
- 1.18.0 — 2026-05-09
- 1.17.0 — 2026-05-06
- 1.15.0 — 2026-05-06
- 1.14.0 — 2023-10-09
- 1.13.0 — 2023-08-14
- 1.12.0 — 2023-05-03
- 1.11.0 — 2023-04-26
- 1.10.0 — 2022-09-29
- 1.9.0 — 2021-08-17
- 1.8.0 — 2021-06-20
- 1.7.0 — 2021-06-18
- … 8 more at https://npm.io/package/lunr-languages/versions
## README
# Lunr Languages — Multilingual Search for AI, RAG & Local-First Apps
> **Used by 18k+ projects • ~300k weekly downloads**
Lunr Languages is an extension for Lunr.js that enables **fast, multilingual full-text search** across dozens of languages — in the browser or Node.js.
Originally built for classic search, it is now widely used as a **lightweight retrieval layer in AI systems**, including:
* Retrieval-Augmented Generation (RAG)
* Hybrid search (keyword + vector)
* Local-first / edge AI apps
* Static site search and documentation search
⭐ If this project saves you time or powers something important, consider starring it or supporting its maintenance.
---
## Supported Languages
*  German
*  French
*  Spanish2
*  Italian
*  Dutch
*  Danish
*  Portuguese
*  Polish
*  Finnish
*  Romanian
*  Hungarian
*  Russian
*  Norwegian
*  Swedish
*  Turkish
*  Japanese
*  Thai
*  Arabic
*  Chinese1
*  Vietnamese
*  Sanskrit
*  Kannada
*  Telugu
*  Hindi
*  Tamil
*  Korean
*  Armenian
*  Hebrew
*  Greek
→ [Contribute a new language](CONTRIBUTING.md)
---
1 Chinese tokenization uses `Intl.Segmenter` with CJK bigrams by default, which works in modern browsers and Node.js without native dependencies. In Node.js, if `@node-rs/jieba` is installed, Lunr Languages uses it automatically for higher-quality Jieba segmentation. Browsers must support `Intl.Segmenter`; there is no frontend fallback.
2 Spanish includes an opt-in `lunr.es.accentFold` pipeline function for Lunr 2 indexes that should match user queries with omitted accents, such as `respiracion` matching `Respiración`, without replacing the default Spanish stemmer.
---
## Why Lunr Languages in an AI world?
Modern AI systems don’t replace search — they **depend on it**.
Before an LLM can generate an answer, it needs **relevant context**. That’s where Lunr Languages fits:
### 🔎 Fast and consistent lexical retrieval
Filter thousands of documents down to a small candidate set before embedding or reranking.
### 🌍 Multilingual support out of the box
Tokenization, stemming, and stopwords for 30+ languages — still a hard problem in AI pipelines.
### ⚡ Zero infrastructure
Runs entirely in the browser or Node.js. No vector DB required.
### 🔒 Privacy-friendly / offline-ready
Perfect for:
* in-browser AI assistants
* local knowledge bases
* on-device search
---
## Example: Hybrid Search (Keyword + AI)
```text
User query
→ Lunr (keyword search, multilingual)
→ top 100–500 documents
→ embeddings / reranker
→ LLM generates answer
```
Lunr Languages improves **recall and precision**, especially for:
* non-English content
* inflected languages
* mixed-language datasets
---
## Installation
```bash
npm install lunr-languages
```
---
## Usage
### Basic example (German)
```javascript
const lunr = require('lunr');
require('lunr-languages/lunr.stemmer.support')(lunr);
require('lunr-languages/lunr.de')(lunr);
const idx = lunr(function () {
this.use(lunr.de);
this.field('title', { boost: 10 });
this.field('body');
this.add({ title: 'Dokument', body: 'Beispieltext' });
});
```
The existing CommonJS usage is still supported. Modern runtimes and TypeScript projects can import the same subpath modules:
```javascript
import lunr from 'lunr';
import stemmerSupport from 'lunr-languages/lunr.stemmer.support';
import de from 'lunr-languages/lunr.de';
stemmerSupport(lunr);
de(lunr);
```
Type declarations are included for the registration modules and the Lunr properties they install, including `lunr.multiLanguage`.
For Spanish indexes on Lunr 2, you can opt into accent-insensitive matching by expanding accented tokens before stemming:
```js
require('lunr-languages/lunr.stemmer.support')(lunr);
require('lunr-languages/lunr.es')(lunr);
var idx = lunr(function () {
this.use(lunr.es);
this.pipeline.before(lunr.es.stemmer, lunr.es.accentFold);
this.searchPipeline.before(lunr.es.stemmer, lunr.es.accentFold);
this.field('body');
this.add({ id: 1, body: 'Respiración' });
});
```
---
## Multi-language indexing
```javascript
require('lunr-languages/lunr.multi')(lunr);
const idx = lunr(function () {
this.use(lunr.multiLanguage('en', 'ru', 'de'));
this.field('title');
this.field('body');
});
```
---
## Chinese Tokenization
Chinese support is designed to work without mandatory native binaries:
* In browsers, `lunr.zh` uses `Intl.Segmenter` plus CJK bigrams. If `Intl.Segmenter` is unavailable, it logs an error and throws because there is no bundled browser fallback.
* In Node.js, `lunr.zh` first tries to load `@node-rs/jieba`. If it is installed, it is used for better Chinese segmentation. If it is not installed, Lunr Languages logs an informational message and falls back to `Intl.Segmenter` plus CJK bigrams.
* If neither `@node-rs/jieba` nor `Intl.Segmenter` is available in Node.js, Chinese tokenization logs an error and throws.
The `Intl.Segmenter` fallback avoids native package supply-chain risk and works well for lightweight search, but it is not identical to Jieba. Bigrams improve recall for common two-character search terms such as `车主` and `学姐`, while Jieba generally provides better precision and ranking for serious Chinese search.
To opt into Jieba tokenization in Node.js:
```bash
npm install @node-rs/jieba
```
---
## Where this fits in modern architectures
Lunr Languages is commonly used as:
* **Pre-filter for vector search**
* **Fallback when embeddings fail**
* **Client-side retrieval for AI apps**
* **Static / documentation search**
👉 In practice, **hybrid search (keyword + vector) performs best**
---
## How it works
To provide high-quality search across languages:
* **Tokenization** — language-aware splitting (including Japanese, Chinese, etc.)
* **Stemming** — matches different word forms
* **Stopword filtering** — removes noise
* **Trimming** — normalizes tokens
These steps improve both **classic search** and **AI retrieval pipelines**.
---
## When to use Lunr Languages vs vector search
Use Lunr Languages when you need:
* fast, deterministic keyword matching
* multilingual normalization
* offline / browser-based search
* low-cost retrieval
Combine with embeddings for:
* semantic similarity
* fuzzy concept matching
---
## Contributing
Want to add a new language?
See [CONTRIBUTING.md](CONTRIBUTING.md)
---
## Support / Sponsorship
Maintained as an open-source project for over a decade.
If your company relies on this in production:
* consider sponsoring
* or contributing improvements
It helps keep the ecosystem stable.
---
## Final note
Even in an AI-first world, **retrieval is the bottleneck**.
Lunr Languages ensures the *right* content reaches your models — fast, locally, and across languages.
---
_Source: https://npm.io/package/lunr-languages · Machine-readable twin of the npm.io package page. Health data is recomputed on every publish._