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] *}

### Модель для входа { #model-for-input }

Если использовать эту модель как входную, как здесь:

from typing import Optional, Union

import pytest
from fastapi.openapi.models import Schema, SchemaType


@pytest.mark.parametrize(
    "type_value",
    [
        "array",
        ["string", "null"],
        None,
    ],
)
def test_allowed_schema_type(
    type_value: Optional[Union[SchemaType, list[SchemaType]]],
) -> None:
    """Test that Schema accepts SchemaType, List[SchemaType] and None for type field."""

import org.apache.maven.api.di.Singleton;
import org.apache.maven.api.model.Build;
import org.apache.maven.api.model.Model;
import org.apache.maven.api.model.Parent;
import org.apache.maven.api.model.Plugin;
import org.apache.maven.api.model.PluginManagement;
import org.apache.maven.api.model.Repository;
import org.apache.maven.api.model.RepositoryPolicy;
import org.apache.maven.api.services.ModelBuilder;

     */
    private static class MockModelBuilderResult implements ModelBuilderResult {
        private final Model effectiveModel;
        private final Model rawModel;
        private final Model fileModel;

        MockModelBuilderResult(Model effectiveModel, Model rawModel, Model fileModel) {
            this.effectiveModel = effectiveModel;
            this.rawModel = rawModel;

## Zusätzliche JSON-Schemadaten in Pydantic-Modellen { #extra-json-schema-data-in-pydantic-models }

Sie können `examples` („Beispiele“) für ein Pydantic-Modell deklarieren, welche dem generierten JSON-Schema hinzugefügt werden.

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

Diese zusätzlichen Informationen werden unverändert zum für dieses Modell ausgegebenen **JSON-Schema** hinzugefügt und in der API-Dokumentation verwendet.

    page.get_by_role("button", name="GET /items/ Read Items").click()
    page.get_by_role("button", name="Try it out").click()
    # Manually add the screenshot
    page.screenshot(path="docs/en/docs/img/tutorial/header-param-models/image01.png")

    # ---------------------
    context.close()
    browser.close()


process = subprocess.Popen(
    ["fastapi", "run", "docs_src/header_param_models/tutorial001.py"]
)
try:

    page.get_by_role("button", name="POST /login/ Login").click()
    page.get_by_role("button", name="Try it out").click()
    # Manually add the screenshot
    page.screenshot(path="docs/en/docs/img/tutorial/request-form-models/image01.png")

    # ---------------------
    context.close()
    browser.close()


process = subprocess.Popen(
    ["fastapi", "run", "docs_src/request_form_models/tutorial001.py"]
)
try:

            <option value="$PROJECT_DIR$/platforms/core-configuration/kotlin-dsl-tooling-models" />
            <option value="$PROJECT_DIR$/platforms/core-configuration/model-core" />
            <option value="$PROJECT_DIR$/platforms/core-configuration/model-groovy" />
            <option value="$PROJECT_DIR$/platforms/core-configuration/model-reflect" />
            <option value="$PROJECT_DIR$/platforms/core-configuration/project-features" />

        <artifactId>modello-maven-plugin</artifactId>
        <configuration>
          <version>1.0.0</version>
          <models>
            <model>src/main/mdo/profiles.mdo</model>
            <model>src/main/mdo/paramdoc.mdo</model>
          </models>
        </configuration>
        <executions>
          <execution>
            <id>modello</id>
            <goals>

@app.get("/items/")
async def read_items(filter_query: Annotated[FilterParams, Query()]):
    return filter_query
```

Read the new docs: [Query Parameter Models](https://fastapi.tiangolo.com/tutorial/query-param-models/).

#### `Header` Parameter Models

Use Pydantic models for `Header` parameters:

```python
from typing import Annotated

from fastapi import FastAPI, Header
from pydantic import BaseModel