pr = repo.get_pull(number)
    label_strs = {label.name for label in pr.get_labels()}
    langs = []
    for label in label_strs:
        if label.startswith("lang-") and not label == lang_all_label:
            langs.append(label[5:])
    logging.info(f"PR #{pr.number} has labels: {label_strs}")
    if not langs or lang_all_label not in label_strs:

     * @param normalizer the normalizer to use for normalizing the search words
     * @param analyzer the analyzer to use for analyzing the search words
     * @param langs the array of languages associated with the search words
     * @return a SuggestItem created from the given search words and associated data
     */

     */
    public FullWidthToHalfWidthAlphabetNormalizer() {
        // nothing
    }

    @Override
    public String normalize(final String text, final String field, final String... langs) {
        if (text == null) {
            return null;
        }
        final char[] chars = new char[text.length()];
        for (int i = 0; i < chars.length; i++) {
            final char c = text.charAt(i);

		t.Fatalf("failed to upsert, got %v", err)
	}

	if langs, err := gorm.G[Language](DB).Where("code = ?", lang.Code).Find(ctx); err != nil {
		t.Errorf("no error should happen when find languages with code, but got %v", err)
	} else if len(langs) != 1 {
		t.Errorf("should only find only 1 languages, but got %+v", langs)
	} else if langs[0].Name != "upsert-new" {

            @Override
            public void init() throws IOException {

            }

            @Override
            public List<String> convert(String text, final String field, String... langs) throws IOException {
                return null;
            }
        };

        final Normalizer normalizer = (text, field, lang) -> null;

        final Suggester suggester = Suggester.builder()

     * @param roles The roles.
     * @param num The number.
     * @param langs The languages.
     * @return The SuggestIndexResponse.
     */
    public SuggestIndexResponse indexFromSearchWord(final String searchWord, final String[] fields, final String[] tags,
            final String[] roles, final int num, final String[] langs) {
        if (logger.isDebugEnabled()) {

    en_path: Annotated[Path, typer.Option(envvar="EN_PATH")],
) -> None:
    assert language != "en", (
        "`en` is the source language, choose another language as translation target"
    )
    langs = get_langs()
    language_name = langs[language]
    lang_path = Path(f"docs/{language}")
    lang_path.mkdir(exist_ok=True)
    lang_prompt_path = lang_path / "llm-prompt.md"

        String[] roles = new String[] { "role1" };
        String[] langs = new String[] { "ja" };

        SuggestAnalyzer analyzer = suggester.settings().analyzer().new DefaultContentsAnalyzer();
        SuggestItem item = defaultContentsParser.parseSearchWords(words, readings, fields, tags, roles, 10, createDefaultReadingConverter(),
                createDefaultNormalizer(), analyzer, langs);

        assertNotNull(item);

            String[] langs = (String[]) propMap.get(QUERY_DEFAULT_LANGUAGES);
            if (langs == null) {
                langs = split(getQueryDefaultLanguages(), ",").get(stream -> stream.map(String::trim).toArray(n -> new String[n]));
                propMap.put(QUERY_DEFAULT_LANGUAGES, langs);

            }
            return normalizeQueryLanguages(langs);
        }

            if (virtualHost != null) {
                tags.add(virtualHost);
            }

            if (sb.length() > 0) {
                final String[] langs = searchLog.getLanguages() == null ? new String[] {} : searchLog.getLanguages().split(",");
                stream(searchLog.getRoles()).of(stream -> stream.forEach(role -> roles.add(role)));