assertTrue(keywords.contains("query"));
    }

    @Test
    public void testGetTermQueryList() {
        // Test with TermQuery
        Term term = new Term("content", "test");
        TermQuery termQuery = new TermQuery(term);
        String[] fields = { "content" };
        List<TermQuery> queryList = SuggestUtil.getTermQueryList(termQuery, fields);
        assertNotNull(queryList);

                    final String term = termTokenList.get(i).getTerm();
                    String reading = readingTokenList.get(i).getTerm();
                    if (Strings.isNullOrEmpty(reading)) {
                        reading = term;
                    }
                    reading = transliterator.transliterate(reading);

                    final int pos = text.indexOf(term, offset);
                    if (pos > 0) {

            while (stream.incrementToken()) {
                final CharTermAttribute att = stream.getAttribute(CharTermAttribute.class);
                final String term = att.toString();
                final int pos = inputStr.indexOf(term, offset);
                if (pos > 0) {
                    final String tmp = inputStr.substring(offset, pos);
                    kanaBuf.append(transliterator.transliterate(tmp));

     * Sets the maximum size of an alpha-numeric term.
     * @param maxAlphanumTermSize The max size of an alpha-numeric term.
     */
    public void setMaxAlphanumTermSize(final int maxAlphanumTermSize) {
        this.maxAlphanumTermSize = maxAlphanumTermSize;
    }

    /**
     * Sets the maximum size of a symbol term.
     * @param maxSymbolTermSize The max size of a symbol term.
     */

 * <li>{@link #ANALYZER_SETTINGS_READING_ANALYZER} - The reading analyzer settings field.</li>
 * <li>{@link #ANALYZER_SETTINGS_READING_TERM_ANALYZER} - The reading term analyzer settings field.</li>
 * <li>{@link #ANALYZER_SETTINGS_NORMALIZE_ANALYZER} - The normalize analyzer settings field.</li>
 * <li>{@link #ANALYZER_SETTINGS_CONTENTS_ANALYZER} - The contents analyzer settings field.</li>

        }

        private String convertToJapaneseReading(String term) {
            // Simple simulation of Japanese reading conversion
            if ("東京".equals(term)) {
                return "トウキョウ";
            } else if ("大阪".equals(term)) {
                return "オオサカ";
            } else {
                return term.toUpperCase();
            }
        }
    }

    /**

# Do not print anything if this is not being used interactively
[ -z "$PS1" ] && return

# Set up attractive prompt
export PS1="\[\e[31m\]tf-docker\[\e[m\] \[\e[33m\]\w\[\e[m\] > "
export TERM=xterm-256color
alias grep="grep --color=auto"
alias ls="ls --color=auto"
# Fix nvidia-docker

* Puedes obtener metadatos del archivo subido.
* Tiene una interfaz `async` <a href="https://docs.python.org/3/glossary.html#term-file-like-object" class="external-link" target="_blank">parecida a un archivo</a>.

        Please follow these instructions carefully to propose a new language translation. 🙏

        This structured process helps ensure translations can be properly maintained long-term.
  - type: checkboxes
    id: checks
    attributes:
      label: Initial Checks
      description: Please confirm and check all the following options.
      options:

| [`Kubernetes`](https://docs.min.io/community/minio-object-store/operations/deployments/kubernetes.html)                                |

## Why is MinIO cloud-native?