import FastText from 'fasttext.js';
import { join } from 'node:path';

export default async function trainAI(ftext, __dirname, config) {
	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: join(__dirname, config.fasttext.loadModel).replace('.bin', ''),
		trainFile: join(__dirname, config.fasttext.trainFile),
		bin: join(__dirname, config.fasttext.bin)
	});

	ftext.unload();

	await ft.train();

	ftext.load();

	return;
}