* @param query the Lucene query to be processed
     * @param boost the boost factor to apply to the query
     * @return the processed OpenSearch QueryBuilder
     */
    public QueryBuilder execute(final QueryContext context, final Query query, final float boost) {
        return filterChain.execute(context, query, boost);
    }

    /**
     * Adds a query command to the processor.
     *

# Extender OpenAPI { #extending-openapi }

Hay algunos casos en los que podrías necesitar modificar el esquema de OpenAPI generado.

En esta sección verás cómo hacerlo.

## El proceso normal { #the-normal-process }

El proceso normal (por defecto) es el siguiente.

Una aplicación (instance) de `FastAPI` tiene un método `.openapi()` que se espera que devuelva el esquema de OpenAPI.

    /**
     * Set of fully qualified class names that have been processed and contain the {@link Named} annotation.
     */
    private final Set<String> processedClasses = new HashSet<>();

    /**
     * Processes classes with the {@link Named} annotation and generates an index file.
     *
     * @param annotations the annotation types requested to be processed

  }

  /**
   * Streams lines from a {@link Readable} object, stopping when the processor returns {@code false}
   * or all lines have been read and returning the result produced by the processor. Does not close
   * {@code readable}. Note that this method may not fully consume the contents of {@code readable}
   * if the processor stops processing early.
   *

Bir container, **ana process** (komut/program) çalıştığı sürece çalışır.

Container'larda normalde **tek bir process** olur. Ancak ana process içinden subprocess'ler başlatmak da mümkündür; böylece aynı container içinde **birden fazla process** olur.

Ama **en az bir çalışan process olmadan** çalışan bir container olamaz. Ana process durursa container da durur.

            ComponentUtil.register(newQueryProcessor, "queryProcessor");

            // Register the command with the new processor
            PrefixQueryCommand newCommand = new PrefixQueryCommand();
            newCommand.register();

            // Verify that the command can process PrefixQuery by executing it
            PrefixQuery query = new PrefixQuery(new Term("field", "test"));

        public org.dbflute.optional.OptionalThingIfPresentAfter ifExecutingNow(
                final java.util.function.Consumer<org.lastaflute.job.subsidiary.SnapshotExecState> oneArgLambda) {
            return processor -> processor.process();
        }

        @Override
        public java.util.Set<org.lastaflute.job.key.LaJobKey> getTriggeredJobKeySet() {
            return Collections.emptySet();
        }

        @Override

  }

  /**
   * Process the bytes of the given input stream using the given processor.
   *
   * @param input the input stream to process
   * @param processor the object to which to pass the bytes of the stream
   * @return the result of the byte processor
   * @throws IOException if an I/O error occurs
   * @since 14.0
   */
  @CanIgnoreReturnValue // some processors won't return a useful result

        public org.dbflute.optional.OptionalThingIfPresentAfter ifExecutingNow(
                final java.util.function.Consumer<org.lastaflute.job.subsidiary.SnapshotExecState> oneArgLambda) {
            return processor -> processor.process();
        }

        @Override
        public java.util.Set<org.lastaflute.job.key.LaJobKey> getTriggeredJobKeySet() {
            return Collections.emptySet();
        }

        @Override

Y también después de que se genere la `response`, antes de devolverla.

Por ejemplo, podrías añadir un custom header `X-Process-Time` que contenga el tiempo en segundos que tomó procesar la request y generar una response:

{* ../../docs_src/middleware/tutorial001_py310.py hl[10,12:13] *}

/// tip | Consejo