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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Natural language detection library for Rust. Try demo online: https://whatlang.org/
| Date | Stars |
|---|---|
| 2026-07-24 | 1084 |
| 2026-07-25 | 1084 |
| 2026-07-28 | 1084 |
| 2026-07-30 | 1084 |
| 2026-08-06 | 1084 |
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<p align="center"><img width="160" src="https://raw.githubusercontent.com/greyblake/whatlang-rs/master/misc/logo/whatlang-logo.svg" alt="Whatlang - rust library for natural language detection"></p>
<h1 align="center">Whatlang</h1>
<p align="center">Natural language detection for Rust with focus on simplicity and performance.</p>
<p align="center"><a href="https://whatlang.org/" target="_blank">Try online demo.</a></p>
<p align="center">
<a href="https://github.com/greyblake/whatlang-rs/actions/workflows/ci.yml" rel="nofollow"><img src="https://github.com/greyblake/whatlang-rs/actions/workflows/ci.yml/badge.svg" alt="Build Status"></a>
<a href="https://raw.githubusercontent.com/greyblake/whatlang-rs/master/LICENSE" rel="nofollow"><img src="https://img.shields.io/badge/license-MIT-blue.svg" alt="License"></a>
<a href="https://docs.rs/whatlang" rel="nofollow"><img src="https://docs.rs/whatlang/badge.svg" alt="Documentation"></a>
<p>
[](https://stand-with-ukraine.pp.ua/)
## Content
* [Features](#features)
* [Get started](#get-started)
* [Who uses Whatlang?](#who-uses-whatlang)
* [Documentation](https://docs.rs/whatlang)
* [Supported languages](https://github.com/greyblake/whatlang-rs/blob/master/SUPPORTED_LANGUAGES.md)
* [Feature toggles](#feature-toggles)
* [How does it work?](#how-does-it-work)
* [Make tasks](#make-tasks)
* [Comparison with alternatives](#comparison-with-alternatives)
* [Ports and clones](#ports-and-clones)
* [Donations](#donations)
* [Derivation](#derivation)
* [License](#license)
* [Contributors](#contributors)
## Features
* Supports [70 languages](https://github.com/greyblake/whatlang-rs/blob/master/SUPPORTED_LANGUAGES.md)
* 100% written in Rust
* Lightweight, fast and simple
* Recognizes not only a language, but also a script (Latin, Cyrillic, etc)
* Provides reliability information
## Get started
Example:
```rust
use whatlang::{detect, Lang, Script};
fn main() {
let text = "Ĉu vi ne volas eklerni Esperanton? Bonvolu! Estas unu de la plej bonaj aferoj!";
let info = detect(text).unwrap();
assert_eq!(info.lang(), Lang::Epo);
assert_eq!(info.script(), Script::Latin);
assert_eq!(info.confidence(), 1.0);
assert!(info.is_reliable());
}
```
For more details (e.g. how to blacklist some languages) please check the [documentation](https://docs.rs/whatlang).
## Who uses Whatlang?
Whatlang is used within the following big projects as direct or indirect dependency for language recognition.
You're gonna be in a great company using Whatlang:
* [Sonic](https://github.com/valeriansaliou/sonic) - fast, lightweight and schema-less search backend in Rust.
* [Meilisearch](https://github.com/meilisearch) - an open-source, easy-to-use, blazingly fast, and hyper-relevant search engine built in Rust.
## Feature toggles
| Feature | Description |
|-------------|---------------------------------------------------------------------------------------|
| `enum-map` | `Lang` and `Script` implement `Enum` trait from [enum-map](https://docs.rs/enum-map/) |
| `arbitrary` | Support [Arbitrary](https://crates.io/crates/arbitrary) |
| `serde` | Implements `Serialize` and `Deserialize` for `Lang` and `Script` |
| `dev` | Enables `whatlang::dev` module which provides some internal API.<br/> It exists for profiling purposes and normal users are discouraged to to rely on this API. |
## How does it work?
### How does the language recognition work?
The algorithm is based on the trigram language models, which is a particular case of n-grams.
To understand the idea, please check the original whitepaper [Cavnar and Trenkle '94: N-Gram-Based Text Categorization'](https://www.researchgate.net/publication/2375544_N-Gram-Based_Text_Categorization).
### How is `is_reliExcerpt of 7,012 characters
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:c2df48358c1bd679, topic:nlp, topic:text-classification