SuggestItem.Kind[] kinds1 = { SuggestItem.Kind.QUERY };
        SuggestItem.Kind[] kinds2 = { SuggestItem.Kind.DOCUMENT, SuggestItem.Kind.QUERY };

        SuggestItem.Kind[] result = SuggestItem.concatKinds(kinds1, kinds2);

        assertNotNull(result);
        assertEquals(2, result.length); // Should not have duplicates
        assertTrue(Arrays.asList(result).contains(SuggestItem.Kind.QUERY));

        QueryContext context = new QueryContext("*:*", false);
        MatchAllDocsQuery query = new MatchAllDocsQuery();
        float boost = 1.0f;

        QueryBuilder result = matchAllQueryCommand.execute(context, query, boost);

        assertNotNull(result);
        assertTrue(result instanceof MatchAllQueryBuilder);

        // Verify the query builder generates correct JSON

</p>
<p align="center">
    FastAPI framework, alte prestazioni, facile da imparare, rapido da implementare, pronto per il rilascio in produzione
</p>

<p align="center">
<a href="https://github.com/fastapi/fastapi/actions?query=workflow%3ATest+event%3Apush+branch%3Amaster" target="_blank">
    <img src="https://github.com/fastapi/fastapi/actions/workflows/test.yml/badge.svg?event=push&branch=master" alt="Test">
</a>

                        .status(ApiResult.Status.OK)
                        .result());
    }

    /**
     * Retrieves a specific related query setting by ID.
     *
     * @param id the ID of the related query to retrieve
     * @return JSON response containing the related query configuration
     */
    // GET /api/admin/relatedquery/setting/{id}
    @Execute
    public JsonResponse<ApiResult> get$setting(final String id) {

                "Unknown q: " + query.getClass() + " => " + query);
    }

    /**
     * Converts a wildcard query to an appropriate OpenSearch QueryBuilder.
     *
     * @param context The query context containing field and search information
     * @param wildcardQuery The Lucene wildcard query to convert
     * @param boost The boost factor to apply to the query
     * @return The converted OpenSearch QueryBuilder

     * The search is performed using the current virtual host context and
     * the query term is converted to lowercase for case-insensitive matching.
     *
     * @param query the search term to find related queries for
     * @return an array of related query strings, or empty array if none found
     */
    public String[] getRelatedQueries(final String query) {
        final String key = ComponentUtil.getVirtualHostHelper().getVirtualHostKey();

///

## Modellattribute deklarieren

Dann können Sie `Field` mit Modellattributen deklarieren:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[11:14] *}

`Field` funktioniert genauso wie `Query`, `Path` und `Body`, es hat die gleichen Parameter, usw.

/// note | Technische Details

{* ../../docs_src/path_params_numeric_validations/tutorial006_an_py39.py hl[13] *}

## Pour résumer

Avec `Query`, `Path` (et d'autres que vous verrez plus tard) vous pouvez déclarer des métadonnées et des validations de chaînes de la même manière qu'avec les [Paramètres de requête et validations de chaînes](query-params-str-validations.md){.internal-link target=_blank}.

Et vous pouvez également déclarer des validations numériques :

import org.codelibs.fess.unit.UnitFessTestCase;
import org.codelibs.fess.util.ComponentUtil;
import org.dbflute.util.DfTypeUtil;
import org.opensearch.index.query.BoolQueryBuilder;
import org.opensearch.index.query.QueryBuilder;
import org.opensearch.index.query.QueryBuilders;
import org.opensearch.index.query.TermQueryBuilder;

public class BooleanQueryCommandTest extends QueryTestBase {

    private BooleanQueryCommand booleanQueryCommand;

## 🌃

⏮️ `Query`, `Path` (& 🎏 👆 🚫 👀) 👆 💪 📣 🗃 & 🎻 🔬 🎏 🌌 ⏮️ [🔢 🔢 & 🎻 🔬](query-params-str-validations.md){.internal-link target=_blank}.

& 👆 💪 📣 🔢 🔬:

* `gt`: `g`🅾 `t`👲
* `ge`: `g`🅾 🌘 ⚖️ `e`🅾
* `lt`: `l`👭 `t`👲
* `le`: `l`👭 🌘 ⚖️ `e`🅾

/// info

`Query`, `Path`, & 🎏 🎓 👆 🔜 👀 ⏪ 🏿 ⚠ `Param` 🎓.