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(

  - author: Kaustubh Gupta
    author_link: https://medium.com/@kaustubhgupta1828/
    link: https://www.analyticsvidhya.com/blog/2021/06/deploying-ml-models-as-api-using-fastapi-and-heroku/
    title: Deploying ML Models as API Using FastAPI and Heroku
  - link: https://jarmos.netlify.app/posts/using-github-actions-to-deploy-a-fastapi-project-to-heroku/

`response_model` receives the same type you would declare for a Pydantic model field, so, it can be a Pydantic model, but it can also be, e.g. a `list` of Pydantic models, like `List[Item]`.

FastAPI will use this `response_model` to do all the data documentation, validation, etc. and also to **convert and filter the output data** to its type declaration.

!!! tip

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.

            if route.callbacks:
                callback_flat_models.extend(get_fields_from_routes(route.callbacks))
            params = get_flat_params(route.dependant)
            request_fields_from_routes.extend(params)

    flat_models = callback_flat_models + list(
        body_fields_from_routes + responses_from_routes + request_fields_from_routes
    )
    return flat_models


def get_openapi(
    *,
    title: str,

```Python hl_lines="1  10-13  21-24"
{!../../../docs_src/sql_databases/sql_app/models.py!}
```

### ✍ 💛

🔜 ✍ 💛.

👉, 👥 ⚙️ `relationship` 🚚 🇸🇲 🐜.

👉 🔜 ▶️️, 🌅 ⚖️ 🌘, "🎱" 🔢 👈 🔜 🔌 💲 ⚪️➡️ 🎏 🏓 🔗 👉 1️⃣.

```Python hl_lines="2  15  26"
{!../../../docs_src/sql_databases/sql_app/models.py!}
```

```Python hl_lines="1  10-13  21-24"
{!../../../docs_src/sql_databases/sql_app/models.py!}
```

### 创建关系

现在创建关系。

为此，我们使用SQLAlchemy  ORM提供的`relationship`。

这将或多或少会成为一种“神奇”属性，其中表示该表与其他相关的表中的值。

```Python hl_lines="2  15  26"
{!../../../docs_src/sql_databases/sql_app/models.py!}
```

当访问 user 中的属性`items`时，如 中`my_user.items`，它将有一个`Item`SQLAlchemy 模型列表（来自`items`表），这些模型具有指向`users`表中此记录的外键。

🆖, 🕐❔ 🛬 📚 🎚, 💖 `get_users`, 👥 🔗 🤙 `list`, 💖:

```Python
list(models.User.select())
```

👉 🎏 🤔 👈 👥 ✔️ ✍ 🛃 `PeeweeGetterDict`. ✋️ 🛬 🕳 👈 ⏪ `list` ↩️ `peewee.ModelSelect` `response_model` *➡ 🛠️* ⏮️ `List[models.User]` (👈 👥 🔜 👀 ⏪) 🔜 👷 ☑.

## 👑 **FastAPI** 📱

& 🔜 📁 `sql_app/main.py` ➡️ 🛠️ & ⚙️ 🌐 🎏 🍕 👥 ✍ ⏭.

### ✍ 💽 🏓

              <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>

    disabled = user_dict["disabled"],
    hashed_password = user_dict["hashed_password"],
)
```

!!! info
    For a more complete explanation of `**user_dict` check back in [the documentation for **Extra Models**](../extra-models.md#about-user_indict){.internal-link target=_blank}.

## Return the token

The response of the `token` endpoint must be a JSON object.