extras.subList(MAX_EXTRAS, extras.size()).clear();
          throw multiples(true);
        }
        return this;
      }
    }

    @IgnoreJRERequirement // see enclosing class (whose annotation Animal Sniffer ignores here...)
    Optional<Object> getOptional() {
      if (extras.isEmpty()) {
        return Optional.ofNullable(element);
      } else {
        throw multiples(false);
      }
    }

  /*
   * If we make these calls inline inside toImmutableSortedMultiset, we get an Animal Sniffer error,
   * despite the @IgnoreJRERequirement annotation there. My assumption is that, because javac
   * generates a synthetic method for the body of the lambda, the actual method calls that Animal
   * Sniffer is flagging don't appear inside toImmutableSortedMultiset but rather inside that

 *
 * @since 4.0.0
 */
@Experimental
@Immutable
public interface ModelBuilderRequest {

    /**
     * Denotes minimal validation of POMs. This validation level is meant for processing of POMs from repositories
     * during metadata retrieval.
     */
    int VALIDATION_LEVEL_MINIMAL = 0;

    /**
     * Denotes validation as performed by Maven 2.0. This validation level is meant as a compatibility mode to allow

        request.projectBuild(true);
        request.session(InternalSession.from(session));
        request.source(ModelSource.fromPath(src));
        request.validationLevel(ModelBuilderRequest.VALIDATION_LEVEL_MINIMAL);
        request.locationTracking(false);
        request.modelResolver(modelResolver);
        request.transformerContextBuilder(modelBuilder.newTransformerContextBuilder());

That will raise the `WebSocketDisconnect` exception, and all the other clients will receive a message like:

```
Client #1596980209979 left the chat
```

!!! tip
    The app above is a minimal and simple example to demonstrate how to handle and broadcast messages to several WebSocket connections.

![ReDoc](https://fastapi.tiangolo.com/img/index/index-06-redoc-02.png)

### Zusammenfassung

Zusammengefasst deklarieren Sie **einmal** die Typen von Parametern, Body, etc. als Funktionsparameter.

Das machen Sie mit modernen Standard-Python-Typen.

Sie müssen keine neue Syntax, Methoden oder Klassen einer bestimmten Bibliothek usw. lernen.

                                .withRemoteRepositories(
                                        request.getModelRepositoryHolder().getRepositories()))
                        .validationLevel(ModelBuilderRequest.VALIDATION_LEVEL_MINIMAL)
                        .systemProperties(request.getSystemProperties())
                        .userProperties(request.getUserProperties())
                        .source(importSource)

    *   Note: This feature will be enabled by default in an upcoming version of
        TensorFlow.

*   `tf.experimental.dtensor`: Added DTensor, an extension to TensorFlow for
    large-scale modeling with minimal changes to user code. You are welcome to
    try it out, though be aware that the DTensor API is experimental and up-to
    backward-incompatible changes. DTensor and Keras integration is published

* ✏️ Fix tooltips for light/dark theme toggler in docs. PR [#9588](https://github.com/tiangolo/fastapi/pull/9588) by [@pankaj1707k](https://github.com/pankaj1707k).
* 🔧 Set minimal hatchling version needed to build the package. PR [#9240](https://github.com/tiangolo/fastapi/pull/9240) by [@mgorny](https://github.com/mgorny).