import FastText from 'fasttext.js';
const ft = new FastText({
    train: {
        // number of concurrent threads
        thread: 8,
        // verbosity level [2]
        verbose: 4,
        // number of negatives sampled [5]
        neg: 7,
        // loss function {ns, hs, softmax} [ns]
        loss: 'ns',
        // learning rate [0.05]
        lr: 1,
        // change the rate of updates for the learning rate [100]
        lrUpdateRate: 1000,
        // max length of word ngram [1]
        wordNgrams: 5,
        // minimal number of word occurences
        minCount: 1,
        // minimal number of word occurences
        minCountLabel: 1,
        // size of word vectors [100]
        dim: 100,
        // size of the context window [5]
        ws: 5,
        //  number of epochs [5]
        epoch: 20,
        // number of buckets [2000000]
        bucket: 2000000,
        // min length of char ngram [3]
        minn: process.env.TRAIN_MINN || 3,
        // max length of char ngram [6]
        maxn: process.env.TRAIN_MAXN || 6,
        // sampling threshold [0.0001]
        t: 0.0001,
        // load pre trained word vectors from unsupervised model
        pretrainedVectors: ''
    },
    serializeTo: '/workspaces/revanced-helper/server/model/model',
    trainFile: '/workspaces/revanced-helper/server/model/train.tsv',
});

export default async function trainAI(unload, load) {
    //unload();

    await ft.train()

  //  load();

    return;
}