How to use the lunr.tokenizer function in lunr

let results = index.query(function() {
		// exact matches should have the highest boost
		this.term(lunr.tokenizer(query), { boost: 100 });

		// prefix matches should be boosted slightly
		this.term(query, { boost: 10, usePipeline: false, wildcard: lunr.Query.wildcard.TRAILING });

		// finally, try a fuzzy search with character 2, without any boost
		this.term(query, { boost: 5, usePipeline: false, editDistance: 2 });
	});
	return results.slice(0, numValues);

function makeSnippet( doc, query ) {
	// generate a regex of the form /[^a-zA-Z](term1|term2)/ for the query "term1 term2"
	const termRegexMatchers = lunr.tokenizer( query ).map( term => escapeRegexString( term ) );
	const termRegexString = '[^a-zA-Z](' + termRegexMatchers.join( '|' ) + ')';
	const termRegex = new RegExp( termRegexString, 'gi' );
	const snippets = [];
	let match;

	// find up to 4 matches in the document and extract snippets to be joined together
	// TODO: detect when snippets overlap and merge them.
	while ( ( match = termRegex.exec( doc.body ) ) !== null && snippets.length < 4 ) {
		const matchStr = match[ 1 ],
			index = match.index + 1,
			before = doc.body.substring( index - SNIPPET_PAD_LENGTH, index ),
			after = doc.body.substring(
				index + matchStr.length,
				index + matchStr.length + SNIPPET_PAD_LENGTH
			);

searchResults = index.query((q) => {
                lunr.tokenizer(query).forEach((token) => {
                    const t = token.toString();
                    q.term(t, { fields: ['name'], wildcard: soWild });
                    q.term(t, { fields: ['subtitle'], wildcard: soWild });
                    q.term(t, { fields: ['login.uris'], wildcard: soWild });
                    q.term(t, {});
                });
            });
        }

function getTokenStream(text, index) {
  return index.pipeline.run(lunr.tokenizer(text));
}

function getTokenStream(text, index) {
  return index.pipeline.run(lunr.tokenizer(text));
}