* 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();

# Corpo - Múltiplos parâmetros { #body-multiple-parameters }

Agora que nós vimos como usar `Path` e `Query`, veremos usos mais avançados de declarações no corpo da requisição.

## Misture `Path`, `Query` e parâmetros de corpo { #mix-path-query-and-body-parameters }

Primeiro, é claro, você pode misturar `Path`, `Query` e declarações de parâmetro no corpo da requisição livremente e o **FastAPI** saberá o que fazer.

from fastapi import FastAPI, Path, Query

app = FastAPI()


@app.get("/items/{item_id}")
async def read_items(
    item_id: int = Path(title="The ID of the item to get"),
    q: str | None = Query(default=None, alias="item-query"),
):
    results = {"item_id": item_id}
    if q:
        results.update({"q": q})

     * Sets the time taken to execute the search query in milliseconds.
     *
     * @param queryTime The query execution time in milliseconds
     */
    public void setQueryTime(final long queryTime) {
        this.queryTime = queryTime;
    }

    /**
     * Sets the actual search query executed against the search engine.
     *
     * @param searchQuery The search query string
     */

            cb.query().setTerm_Wildcard(wrapQuery(keyMatchPager.term));
        }
        if (StringUtil.isNotBlank(keyMatchPager.query)) {
            cb.query().setQuery_Wildcard(wrapQuery(keyMatchPager.query));
        }
        // TODO Long, Integer, String supported only.

        // setup condition
        cb.query().addOrderBy_Term_Asc();

        // search

    }

import org.opensearch.core.xcontent.XContentParser;
import org.opensearch.index.query.AbstractQueryBuilder;
import org.opensearch.index.query.QueryBuilder;
import org.opensearch.index.query.QueryShardContext;

/**
 * A query builder for a stored LTR (Learning to Rank) query.
 * This builder constructs a query that uses a pre-trained LTR model
 * to re-rank search results based on a given set of features.
 */

from typing import Annotated

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(q: Annotated[str | None, Query(alias="item-query")] = None):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

from typing import Union

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(q: Union[str, None] = Query(default=None, alias="item-query")):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

    /**
     * Performs a search operation using the specified query and parameters.
     *
     * @param query the search query string
     * @param params the search request parameters
     * @param userBean the optional user bean for access control
     * @return the search result containing documents and metadata
     */
    @Override

func parsePreSignV4(query url.Values, region string, stype serviceType) (psv preSignValues, aec APIErrorCode) {
	// verify whether the required query params exist.
	aec = doesV4PresignParamsExist(query)
	if aec != ErrNone {
		return psv, aec
	}

	// Verify if the query algorithm is supported or not.
	if query.Get(xhttp.AmzAlgorithm) != signV4Algorithm {