ongjin

ongjin / garu

Public

브라우저에서 직접 실행되는 WebAssembly 기반 형태소 분석기

19
2
100% credibility
Found Apr 01, 2026 at 19 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A lightweight browser-native Korean morphological analyzer that breaks sentences into morphemes and parts-of-speech tags using a compact model and WebAssembly.

How It Works

1
🔍 Discover Garu

You hear about a super-light tool that breaks down Korean sentences into tiny word pieces right in your web browser, no servers needed.

2
📦 Add to your project

Grab the ready-to-use package and drop it into your web app with a quick setup.

3
⚡ Wake up the analyzer

Click to load the brain of your tool – it grabs everything it needs and lights up in moments.

4
📝 Give it Korean text

Type or paste any Korean sentence, like '배가 아파서 약을 먹었다'.

5
✨ See the magic breakdown

Watch it instantly split the sentence into words like '배/명사', '가/조사', '아프/형용사' with their roles.

6
🔄 Try more or tweak

Test on new sentences, grab just the words, or swap in a custom brain for special needs.

🎉 Offline Korean superpowers

Now your web app understands Korean deeply, works everywhere without internet, lightning-fast and tiny.

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Star Growth

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AI-Generated Review

What is garu?

Garu is a Korean morphological analyzer that runs directly in browsers via WebAssembly, breaking text into morphemes with POS tags like a lightweight MeCab alternative. Load a 2MB model, call analyze("배가 아파요"), and get tokens with start/end offsets and scores—no servers or Python runtimes needed. It's Rust under the hood, exposed via npm for JS/TS, perfect for webassembly github pages or rust webassembly github demos.

Why is it gaining traction?

Unlike bulky server-side tools (40MB+ models, latency), garu delivers 90%+ F1 accuracy at <1ms per sentence offline, with npm install garu-ko and a live demo. Extras like nouns extraction and sentence splitting hook JS devs tired of API calls, while webassembly projects github io hosting shines for PWAs. Blazor webassembly github pages users get instant Korean tokenization without backend hacks.

Who should use this?

Frontend devs building Korean search UIs, chat apps, or sentiment tools where offline speed matters. TS authors of Blazor WebAssembly GitHub Pages sites handling user input like Garuda Linux forums or Garum recipes. Avoid if you need full NLP pipelines—pair it with simple JS for token-based features.

Verdict

Grab it for browser Korean NLP prototypes; the demo sells it fast. At 19 stars and 1.0% credibility, it's early—docs are solid but test coverage lags. Solid foundation for webassembly in action github experiments.

(187 words)

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