final List<String> roles = (List<String>) sourceArray[i].get(ELEVATE_WORD_ROLES);
            if (elevateWord != null && boost != null && readings != null && fields != null) {
                elevateWords[i] =
                        new ElevateWord(elevateWord.toString(), Float.parseFloat(boost.toString()), readings, fields, tags, roles);
            }
        }
        return elevateWords;
    }

    /**
     * Add an elevate word.

    public void setUserBoost(final float userBoost) {
        this.userBoost = userBoost;
    }

    /**
     * Sets the readings of the suggest item.
     * @param readings The readings to set.
     */
    public void setReadings(final String[][] readings) {
        this.readings = readings;
    }

    /**
     * Sets the fields of the suggest item.
     * @param fields The fields to set.
     */

        final Map<String, Object> secondLine = new HashMap<>();

        secondLine.put("text", item.getText());

        // reading
        final String[][] readings = item.getReadings();
        for (int i = 0; i < readings.length; i++) {
            secondLine.put("reading_" + i, readings[i]);
        }

        secondLine.put("fields", item.getFields());
        secondLine.put("queryFreq", item.getQueryFreq());

                    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) {

        queryItems[0] = new SuggestItem(new String[] { "検索", "エンジン" }, readings, new String[] { "content" }, 1, 0, -1, tags, roles, null,
                SuggestItem.Kind.DOCUMENT);

        String[][] readings2 = new String[2][];
        readings2[0] = new String[] { "zenbun", "fuga" };
        readings2[1] = new String[] { "kensaku", "fuga" };
        String[] tags2 = new String[] { "tag3" };

                    continue;
                }

                String reading = getReadingFromAttribute(stream);
                if (Strings.isNullOrEmpty(reading)) {
                    reading = transliterator.transliterate(att.toString());
                }
                kanaBuf.append(reading);
                offset += term.length();
            }
        }

    }

    /**
     * Sets the reading converter.
     * @param readingConverter The reading converter.
     * @return This builder instance.
     */
    public SuggesterBuilder readingConverter(final ReadingConverter readingConverter) {
        this.readingConverter = readingConverter;
        return this;
    }

    /**
     * Sets the contents reading converter.

 * A chain of {@link ReadingConverter} implementations that applies each converter in sequence to generate possible reading variations of a given text.
 * It maintains a list of ReadingConverter instances and iterates through them, applying each converter to the input text and accumulating the results.
 * The chain stops processing when the maximum number of readings is reached.
 */
public class ReadingConverterChain implements ReadingConverter {
    /**

    /**
     * Analyzes the given text and returns a list of tokens along with their readings.
     *
     * @param text the text to analyze
     * @param field the field associated with the text
     * @param lang the language of the text
     * @return a list of analyzed tokens with their readings
     */
    List<AnalyzeToken> analyzeAndReading(String text, String field, String lang);

 */
package org.codelibs.fess.suggest.index.contents.document;

import java.io.Closeable;
import java.util.Map;

/**
 * Interface for reading documents and extracting their contents into a map.
 * Implementations of this interface should provide the logic for reading
 * documents and converting them into a key-value structure.
 *
 * <p>This interface extends {@link java.io.Closeable}, so implementations