这样，你就能兼得两方面的优势：带有**工具支持**的类型注解和**数据过滤**。

## 在文档中查看 { #see-it-in-the-docs }

当你查看自动文档时，你会看到输入模型和输出模型都会有各自的 JSON Schema：

<img src="/img/tutorial/response-model/image01.png">

并且两个模型都会用于交互式 API 文档：

<img src="/img/tutorial/response-model/image02.png">

## 其他返回类型注解 { #other-return-type-annotations }

有些情况下你会返回一些不是有效 Pydantic 字段的内容，并在函数上做了相应注解，只是为了获得工具链（编辑器、mypy 等）的支持。

## Use Case { #use-case }

Let's start with an example **use case** and then see how to solve it with this.

Let's imagine that you have some **machine learning models** that you want to use to handle requests. 🤖

The same models are shared among requests, so, it's not one model per request, or one per user or something similar.

  specific language governing permissions and limitations
  under the License.

-->

<model xmlns="http://codehaus-plexus.github.io/MODELLO/2.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xsi:schemaLocation="http://codehaus-plexus.github.io/MODELLO/2.0.0 https://codehaus-plexus.github.io/modello/xsd/modello-2.0.0.xsd"
  xml.namespace="http://maven.apache.org/EXTENSIONS/${version}"

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":

specific language governing permissions and limitations
under the License.
-->

<model xmlns="http://modello.codehaus.org/MODELLO/1.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xsi:schemaLocation="http://modello.codehaus.org/MODELLO/1.0.0 http://modello.codehaus.org/xsd/modello-1.0.0.xsd"
  xml.namespace="http://maven.apache.org/PROFILES/${version}"

    page.get_by_role("button", name="Try it out").click()
    page.get_by_role("heading", name="Servers").click()
    # Manually add the screenshot
    page.screenshot(path="docs/en/docs/img/tutorial/query-param-models/image01.png")

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


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

 * under the License.
 */
package org.apache.maven.model.building;

import java.util.EnumSet;
import java.util.List;
import java.util.Set;

import org.apache.maven.model.Model;
import org.apache.maven.model.io.ModelParseException;

/**
 * Collects problems that are encountered during model building. The primary purpose of this component is to account for

### Modelo para Entrada { #model-for-input }

Si usas este modelo como entrada, como aquí:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:15] hl[14] *}

...entonces el campo `description` **no será requerido**. Porque tiene un valor por defecto de `None`.

### Modelo de Entrada en la Documentación { #input-model-in-docs }

### Modelo para Entrada { #model-for-input }

Se você usar esse modelo como entrada, como aqui:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:15] hl[14] *}

... então o campo `description` **não será obrigatório**. Porque ele tem um valor padrão de `None`.

### Modelo de Entrada na Documentação { #input-model-in-docs }

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] *}

That extra info will be added as-is to the output **JSON Schema** for that model, and it will be used in the API docs.