import org.apache.maven.api.model.Exclusion;
import org.apache.maven.api.model.Model;
import org.apache.maven.api.services.BuilderProblem.Severity;
import org.apache.maven.api.services.ModelBuilderRequest;
import org.apache.maven.api.services.ModelProblem.Version;
import org.apache.maven.api.services.ModelProblemCollector;
import org.apache.maven.api.services.model.*;

/**
 * Handles the import of dependency management from other models into the target model.

            @Override
            public Model getRawModel(Path from, String gId, String aId) {
                Model model = findRawModel(from, gId, aId);
                if (model != null) {
                    context.modelByGA.put(new GAKey(gId, aId), new Holder(model));
                    context.modelByPath.put(model.getPomFile(), new Holder(model));
                }
                return model;
            }

            @Override

* Automatyczna dokumentacja modelu danych za pomocą <a href="https://json-schema.org/" class="external-link" target="_blank"><strong>JSON Schema</strong></a> (ponieważ OpenAPI bazuje na JSON Schema).

              <goal>xdoc</goal>
            </goals>
            <phase>pre-site</phase>
            <configuration>
              <version>1.0.0</version>
              <models>
                <model>src/main/mdo/extension.mdo</model>
              </models>
            </configuration>
          </execution>
        </executions>
      </plugin>
      <plugin>
        <groupId>org.codehaus.mojo</groupId>

        Doc(
            """
            Pydantic's `include` parameter, passed to Pydantic models to set the
            fields to include.
            """
        ),
    ] = None,
    exclude: Annotated[
        Optional[IncEx],
        Doc(
            """
            Pydantic's `exclude` parameter, passed to Pydantic models to set the
            fields to exclude.
            """
        ),
    ] = None,

    boolean isResolveDependencies();

    /**
     * Controls the level of validation to perform on processed models. By default, models are validated in strict mode.
     *
     * @param validationLevel The level of validation to perform on processed models, e.g.
     *            {@link org.apache.maven.model.building.ModelBuildingRequest#VALIDATION_LEVEL_STRICT}.
     * @return This configuration, never {@code null}.
     */

    def _model_rebuild(model: Type[BaseModel]) -> None:
        model.model_rebuild()

    def _model_dump(
        model: BaseModel, mode: Literal["json", "python"] = "json", **kwargs: Any
    ) -> Any:
        return model.model_dump(mode=mode, **kwargs)

    def _get_model_config(model: BaseModel) -> Any:
        return model.model_config

    def get_schema_from_model_field(

## Create the Pydantic models

Now let's check the file `sql_app/schemas.py`.

!!! tip
    To avoid confusion between the Peewee *models* and the Pydantic *models*, we will have the file `models.py` with the Peewee models, and the file `schemas.py` with the Pydantic models.

    These Pydantic models define more or less a "schema" (a valid data shape).

from fastapi import Depends, FastAPI, HTTPException, Request, Response
from sqlalchemy.orm import Session

from . import crud, models, schemas
from .database import SessionLocal, engine

models.Base.metadata.create_all(bind=engine)

app = FastAPI()


@app.middleware("http")
async def db_session_middleware(request: Request, call_next):
    response = Response("Internal server error", status_code=500)
    try:

     */
    private static final Map<String, Model> SUPER_MODELS = new ConcurrentHashMap<>();

    @Inject
    public DefaultSuperPomProvider(ModelProcessor modelProcessor) {
        this.modelProcessor = modelProcessor;
    }

    @Override
    public Model getSuperPom(String version) {
        return SUPER_MODELS.computeIfAbsent(Objects.requireNonNull(version), v -> readModel(version, v));
    }