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

/**
 * Provides the super POM that all models implicitly inherit from.
 *
 * @since 4.0.0
 */
@Experimental
public interface SuperPomProvider extends Service {

    /**
     * Gets the super POM for the specified model version.
     *

```JSON
{
  "title": "towel",
  "size": "XL"
}
```

受信したボディを含むデータが無効であることを示すレスポンスが表示されます:

```JSON hl_lines="12 13 14 15"
{
  "detail": [
    {
      "loc": [
        "body",
        "size"
      ],
      "msg": "value is not a valid integer",
      "type": "type_error.integer"
    }
  ],
  "body": {
    "title": "towel",
    "size": "XL"
  }
}
```

 * specific language governing permissions and limitations
 * under the License.
 */
package org.apache.maven.model.superpom;

import org.apache.maven.model.Model;

/**
 * Provides the super POM that all models implicitly inherit from.
 *
 * @deprecated use {@code org.apache.maven.api.services.ModelBuilder} instead
 */
@Deprecated(since = "4.0.0")
public interface SuperPomProvider {

    /**

# Declare Request Example Data { #declare-request-example-data }

You can declare examples of the data your app can receive.

Here are several ways to do it.

## Extra JSON Schema data in Pydantic models { #extra-json-schema-data-in-pydantic-models }

You can declare `examples` for a Pydantic model that will be added to the generated JSON Schema.

{* ../../docs_src/schema_extra_example/tutorial001_py310.py hl[13:24] *}

import org.apache.maven.api.annotations.Nonnull;
import org.apache.maven.api.toolchain.ToolchainModel;

/**
 * Factory interface for creating toolchain instances from configuration models.
 *
 * <p>This factory is responsible for instantiating concrete toolchain implementations
 * based on toolchain model configurations or default settings.</p>
 *
 * @since 4.0.0
 */
@Experimental
@Consumer

from typing import Annotated, Optional

from annotated_doc import Doc
from fastapi.openapi.models import OpenIdConnect as OpenIdConnectModel
from fastapi.security.base import SecurityBase
from starlette.exceptions import HTTPException
from starlette.requests import Request
from starlette.status import HTTP_401_UNAUTHORIZED


class OpenIdConnect(SecurityBase):
    """
    OpenID Connect authentication class. An instance of it would be used as a

from enum import Enum

from fastapi import FastAPI


class ModelName(str, Enum):
    alexnet = "alexnet"
    resnet = "resnet"
    lenet = "lenet"


app = FastAPI()


@app.get("/models/{model_name}")
async def get_model(model_name: ModelName):
    if model_name is ModelName.alexnet:
        return {"model_name": model_name, "message": "Deep Learning FTW!"}

    if model_name.value == "lenet":

Посмотрим, как это работает, и как это изменить при необходимости.

## Pydantic‑модели для входа и выхода { #pydantic-models-for-input-and-output }

Предположим, у вас есть Pydantic‑модель со значениями по умолчанию, как здесь:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:7] hl[7] *}

import org.apache.maven.model.Model;
import org.apache.maven.model.building.ModelBuildingRequest;
import org.apache.maven.model.building.ModelProblemCollector;

/**
 * Handles the import of dependency management from other models into the target model.
 *
 * @deprecated use {@code org.apache.maven.api.services.ModelBuilder} instead
 */
@Named
@Singleton
@Deprecated(since = "4.0.0")

import org.apache.maven.model.building.ModelProblemCollector;

/**
 * Handles normalization of a model. In this context, normalization is the process of producing a canonical
 * representation for models that physically look different but are semantically equivalent.
 *
 * @deprecated use {@code org.apache.maven.api.services.ModelBuilder} instead
 */
@Deprecated(since = "4.0.0")
public interface ModelNormalizer {