import gradlebuild.docs.dsl.source.model.ClassMetaData
import gradlebuild.docs.dsl.source.model.MethodMetaData
import gradlebuild.docs.dsl.source.model.ParameterMetaData
import gradlebuild.docs.dsl.source.model.PropertyMetaData
import gradlebuild.docs.dsl.source.model.TypeMetaData
import gradlebuild.docs.XmlSpecification
import gradlebuild.docs.dsl.docbook.model.ClassDoc
import gradlebuild.docs.dsl.docbook.model.MethodDoc

Stellen wir uns vor, dass das Laden des Modells **eine ganze Weile dauern** kann, da viele **Daten von der Festplatte** gelesen werden müssen. Sie möchten das also nicht für jeden Request tun.

 * KIND, either express or implied.  See the License for the
 * specific language governing permissions and limitations
 * under the License.
 */
package org.apache.maven.model.building;

/**
 * Defines events that the model builder fires during construction of the effective model. When a listener encounters
 * errors while processing the event, it can report these problems via {@link ModelBuildingEvent#getProblems()}.

import org.apache.maven.artifact.versioning.VersionRange;
import org.apache.maven.bridge.MavenRepositorySystem;
import org.apache.maven.model.Dependency;
import org.apache.maven.model.Plugin;
import org.apache.maven.model.Repository;
import org.apache.maven.model.io.ModelReader;
import org.apache.maven.project.artifact.ArtifactWithDependencies;
import org.apache.maven.settings.Mirror;
import org.apache.maven.settings.Proxy;

import jetbrains.buildServer.configs.kotlin.DslContext
import jetbrains.buildServer.configs.kotlin.buildSteps.GradleBuildStep
import model.CIBuildModel
import model.JsonBasedGradleSubprojectProvider
import model.PerformanceTestCoverage
import model.PerformanceTestType
import model.Stage
import model.StageName
import org.junit.jupiter.api.Assertions.assertEquals
import org.junit.jupiter.api.Test
import java.io.File

					"language-groovy",
					"language-java",
					"language-jvm",
					"language-native",
					"launcher",
					"logging",
					"maven",
					"messaging",
					"model-core",
					"model-groovy",
					"persistent-cache",
					"platform-base",
					"platform-jvm",
					"platform-native",
					"plugin-development",
					"plugin-use",
					"plugins-application",

import org.apache.maven.api.VersionConstraint;
import org.apache.maven.api.annotations.Nonnull;
import org.apache.maven.api.annotations.Nullable;
import org.apache.maven.api.model.DependencyManagement;
import org.apache.maven.api.model.Model;
import org.apache.maven.project.MavenProject;
import org.apache.maven.project.artifact.ProjectArtifact;
import org.eclipse.aether.util.artifact.ArtifactIdUtils;

///

/// tip

If you are wondering, "AlexNet", "ResNet", and "LeNet" are just names of Machine Learning <abbr title="Technically, Deep Learning model architectures">models</abbr>.

///

### Declare a *path parameter*

Then create a *path parameter* with a type annotation using the enum class you created (`ModelName`):

```Python hl_lines="16"

```

Vous pouvez retourner un dictionnaire (`dict`), une liste (`list`), des valeurs seules comme des chaines de caractères (`str`) et des entiers (`int`), etc.

Vous pouvez aussi retourner des models **Pydantic** (qui seront détaillés plus tard).

Il y a de nombreux autres objets et modèles qui seront automatiquement convertis en JSON. Essayez d'utiliser vos favoris, il est fort probable qu'ils soient déjà supportés.

**FastAPI** faz uso dele para que você veja o erro no seu log, caso você utilize um modelo de Pydantic em `response_model`, e seus dados tenham erro.

Contudo, o cliente ou usuário não terão acesso a ele. Ao contrário, o cliente receberá um "Internal Server Error" com o HTTP status code `500`.