You can see those schemas because they were declared with the models in the app.

That information is available in the app's **OpenAPI schema**, and then shown in the API docs (by Swagger UI).

And that same information from the models that is included in OpenAPI is what can be used to **generate the client code**.

### Generate a TypeScript Client

Now that we have the app with the models, we can generate the client code for the frontend.

        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,

import time
from typing import List

from fastapi import Depends, FastAPI, HTTPException

from . import crud, database, models, schemas
from .database import db_state_default

database.db.connect()
database.db.create_tables([models.User, models.Item])
database.db.close()

app = FastAPI()

sleep_time = 10


async def reset_db_state():
    database.db._state._state.set(db_state_default.copy())
    database.db._state.reset()

### Modelo de Entrada na Documentação

Você pode confirmar que na documentação, o campo `description` não tem um **asterisco vermelho**, não é marcado como obrigatório:

<div class="screenshot">
<img src="/img/tutorial/separate-openapi-schemas/image01.png">
</div>

### Modelo para Saída

Mas se você usar o mesmo modelo como saída, como aqui:

//// tab | Python 3.10+

Und Sie können alle Modelle und Daten für die Sicherheitsanforderungen verwenden (in diesem Fall ein Pydantic-Modell `User`).

Sie sind jedoch nicht auf die Verwendung von bestimmten Datenmodellen, Klassen, oder Typen beschränkt.

Möchten Sie eine `id` und eine `email` und keinen `username` in Ihrem Modell haben? Kein Problem. Sie können dieselben Tools verwenden.

     *       {@code {"--module-path", "dir/path1:dir/path2"}} on Unix or
     *       {@code {"--module-path", "dir\path1;dir\path2"}} on Windows.</li>
     *   <li>If this type was created by {@code JavaPathType.patchModule("foo.bar")}, then the method returns
     *       {@code {"--patch-module", "foo.bar=dir/path1:dir/path2"}} on Unix or
     *       {@code {"--patch-module", "foo.bar=dir\path1;dir\path2"}} on Windows.</li>

 ╭─ <font color="#8AE234"><b>Python module file</b></font> ─╮
 │                      │
 │  🐍 main.py          │
 │                      │
 ╰──────────────────────╯

<font color="#3465A4">INFO    </font> Importing module <font color="#4E9A06">main</font>
<font color="#3465A4">INFO    </font> Found importable FastAPI app

{* ../../docs_src/first_steps/tutorial001.py hl[8] *}

Możesz zwrócić `dict`, `list`, pojedynczą wartość jako `str`, `int`, itp.

Możesz również zwrócić modele Pydantic (więcej o tym później).

Istnieje wiele innych obiektów i modeli, które zostaną automatycznie skonwertowane do formatu JSON (w tym ORM itp.). Spróbuj użyć swoich ulubionych, jest bardzo prawdopodobne, że są już obsługiwane.

## Podsumowanie

client = TestClient(app)


def test_get_enums_alexnet():
    response = client.get("/models/alexnet")
    assert response.status_code == 200
    assert response.json() == {"model_name": "alexnet", "message": "Deep Learning FTW!"}


def test_get_enums_lenet():
    response = client.get("/models/lenet")
    assert response.status_code == 200

{!../../docs_src/body/tutorial001.py!}
```

## Crie seu modelo de dados

Então você declara seu modelo de dados como uma classe que herda `BaseModel`.

Utilize os tipos Python padrão para todos os atributos:

```Python hl_lines="7-11"
{!../../docs_src/body/tutorial001.py!}
```