sonai 0.3.0

Generic AI Text Detection for rust
Documentation 
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use std::sync::LazyLock;

use linfa_clustering::KMeans;
use sonai_metrics::{TextMetricFactory, TextMetrics, features_from_metrics, point_confidence};

const AI_CLUSTER: usize =
    include_bytes!(concat!(env!("CARGO_MANIFEST_DIR"), "/model.ai.cluster"))[0] as usize;

static MODEL: LazyLock<KMeans<f64, linfa_nn::distance::L2Dist>> = LazyLock::new(|| {
    let config = bincode::config::standard();
    bincode::serde::decode_from_slice(
        include_bytes!(concat!(env!("CARGO_MANIFEST_DIR"), "/model.kmeans")),
        config,
    )
    .unwrap()
    .0
});

static METRICS: LazyLock<TextMetricFactory> = LazyLock::new(|| TextMetricFactory::new().unwrap());

#[derive(Debug, serde::Serialize)]
pub struct Prediction {
    pub chance_ai: f64,
    pub chance_human: f64,
    pub metrics: TextMetrics,
}

fn _predict(devlog: &str) -> Prediction {
    let sample = METRICS.calculate(devlog);
    let features = features_from_metrics(&[&sample]);
    let features = features.row(0);
    let model = &*MODEL;

    let (_, sims) = point_confidence(model, features);

    let chance_ai = sims.get(AI_CLUSTER).cloned().unwrap_or(0.0) * 100.0;
    let chance_human = 100.0 - chance_ai;

    Prediction {
        metrics: sample,
        chance_ai,
        chance_human,
    }
}

#[cfg(not(target_arch = "wasm32"))]
pub fn predict(devlog: &str) -> Prediction {
    _predict(devlog)
}

#[cfg(target_arch = "wasm32")]
use wasm_bindgen::prelude::*;

#[cfg(target_arch = "wasm32")]
#[wasm_bindgen]
pub fn predict(devlog: &str) -> JsValue {
    serde_wasm_bindgen::to_value(&_predict(devlog)).unwrap()
}