use(BuildableDOMCategory) {
            DslDocModel model = createDslDocModelClosure(loadPluginsMetaData())
            def root = doc.documentElement
            root.section.table.each { Element table ->
                mergeContent(table, model)
            }
            model.classes.each {
                generateDocForType(root.ownerDocument, model, linkRepository, it)
            }
        }

import org.apache.maven.api.annotations.Nonnull;
import org.apache.maven.api.model.Model;

/**
 * A model transformer.
 *
 * @since 4.0.0
 */
@Experimental
public interface ModelTransformer {

    /**
     * Apply a transformation on the file model.
     *
     * @param model the input model
     * @param problems the problem collector to report any issues encountered during transformation

        Model model = Model.newBuilder()
                .groupId("group")
                .location("groupId", InputLocation.of(InputSource.of("model", null)))
                .build();
        StringSearchModelInterpolator interpolator = new StringSearchModelInterpolator();
        interpolator.initialize();
        interpolator.interpolate(new org.apache.maven.model.Model(model), Map.of());
    }

from pydantic import BaseModel

# Deklarieren Sie eine Variable als ein str
# und bekommen Sie Editor-Unterstützung innerhalb der Funktion
def main(user_id: str):
    return user_id


# Ein Pydantic-Modell
class User(BaseModel):
    id: int
    name: str
    joined: date
```

Das kann nun wie folgt verwendet werden:

```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

    /**
     * Injects plugin executions induced by lifecycle bindings into the specified model. The model has already undergone
     * injection of plugin management so any plugins that are injected by lifecycle bindings and are not already present
     * in the model's plugin section need to be subjected to the model's plugin management.
     *
     * @param model The model into which to inject the default plugin executions for its packaging, must not be

    return {"p": p}


class HeaderModelOptionalStr(BaseModel):
    p: str | None = None


@app.get("/model-optional-str")
async def read_model_optional_str(p: Annotated[HeaderModelOptionalStr, Header()]):
    return {"p": p.p}


@pytest.mark.parametrize(
    "path",
    ["/optional-str", "/model-optional-str"],
)
def test_optional_str_schema(path: str):

Es wird von Pydantic **nicht unterstützt**, dass ein Pydantic‑v2‑Modell Felder hat, die als Pydantic‑v1‑Modelle definiert sind, und umgekehrt.

```mermaid
graph TB
    subgraph "❌ Nicht unterstützt"
        direction TB
        subgraph V2["Pydantic-v2-Modell"]
            V1Field["Pydantic-v1-Modell"]
        end
        subgraph V1["Pydantic-v1-Modell"]
            V2Field["Pydantic-v2-Modell"]
        end
    end

import org.apache.maven.model.PluginContainer;
import org.apache.maven.model.PluginExecution;
import org.apache.maven.model.Profile;
import org.apache.maven.model.ReportPlugin;
import org.apache.maven.model.ReportSet;
import org.apache.maven.model.Reporting;
import org.apache.maven.model.building.ModelBuildingRequest;
import org.apache.maven.model.building.ModelProblemCollector;
import org.apache.maven.model.merge.MavenModelMerger;

package configurations

import common.Os
import common.buildScanTagParam
import common.getBuildScanCustomValueParam
import model.CIBuildModel
import model.Stage

class SanityCheck(
    model: CIBuildModel,
    stage: Stage,
) : OsAwareBaseGradleBuildType(os = Os.LINUX, stage = stage, init = {
        id(buildTypeId(model))
        name = "Sanity Check"
        description = "Static code analysis, checkstyle, release notes verification, etc."

    return {"p": p}


class HeaderModelRequiredStr(BaseModel):
    p: str


@app.get("/model-required-str")
async def read_model_required_str(p: Annotated[HeaderModelRequiredStr, Header()]):
    return {"p": p.p}


@pytest.mark.parametrize(
    "path",
    ["/required-str", "/model-required-str"],
)
def test_required_str_schema(path: str):