return buildDefaultQueryBuilder(fessConfig, context, (f, b) -> QueryBuilders.matchPhraseQuery(f, origQuery).boost(b));
        }

        context.addFieldLog(field, termRangeQuery.toString(field));
        final RangeQueryBuilder rangeQuery = QueryBuilders.rangeQuery(field);
        final BytesRef min = termRangeQuery.getLowerTerm();
        if (min != null) {
            if (termRangeQuery.includesLower()) {

import pytest
from dirty_equals import AnyThing, IsOneOf, IsPartialDict
from fastapi import FastAPI, Header
from fastapi.testclient import TestClient
from inline_snapshot import snapshot
from pydantic import BaseModel, Field

app = FastAPI()

# =====================================================================================
# Without aliases


@app.get("/required-list-str")

        final FessConfig fessConfig = ComponentUtil.getFessConfig();
        final String field = getSearchField(context.getDefaultField(), wildcardQuery.getField());
        if (Constants.DEFAULT_FIELD.equals(field)) {
            final String text = wildcardQuery.getTerm().text();
            context.addFieldLog(field, text);
            final String highlightText = StringUtils.strip(text, "*");

}

// FieldNewValuePool field new scan value pool
type FieldNewValuePool interface {
	Get() interface{}
	Put(interface{})
}

// CreateClausesInterface create clauses interface
type CreateClausesInterface interface {
	CreateClauses(*Field) []clause.Interface
}

// QueryClausesInterface query clauses interface
type QueryClausesInterface interface {
	QueryClauses(*Field) []clause.Interface
}

         * Normalizes the given text based on the specified field.
         *
         * @param text  the text to normalize
         * @param field the field to use for normalization
         * @param dummy additional parameters (not used)
         * @return the normalized text
         */
        @Override
        public String normalize(final String text, final String field, final String... dummy) {
            if (text == null) {

    /**
     * Analyzes the given text and returns a list of tokens.
     *
     * @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
     */
    List<AnalyzeToken> analyze(String text, String field, String lang);

    /**
     * Analyzes the given text and returns a list of tokens along with their readings.
     *

                Map.of("_default", List.of("QUERY1")), //
                Set.of("QUERY1"), //

 * a given text based on the specified field and optional language parameters.
 */
public interface Normalizer {
    /**
     * Normalizes the given text.
     * @param text The text to normalize
     * @param field The field name
     * @param langs The language
     * @return The normalized text
     */
    String normalize(String text, String field, String... langs);

    // --------------------------/
    // - Class/Member Variables -/
    // --------------------------/

    /**
     * Field lifecycles.
     */
    private java.util.List<Lifecycle> lifecycles;

    /**
     * Field modelEncoding.
     */
    private String modelEncoding = "UTF-8";

    // -----------/
    // - Methods -/
    // -----------/

    /**

        }

        context.addFieldLog(field, text + "*");
        context.addHighlightedQuery(text);
        if (getQueryFieldConfig().notAnalyzedFieldSet.contains(field)) {
            return QueryBuilders.prefixQuery(field, toLowercaseWildcard(text)).boost(boost);
        }
        return QueryBuilders.matchPhrasePrefixQuery(field, toLowercaseWildcard(text))
                .boost(boost)