## Additional Responses { #additional-responses }

You probably have seen how to declare the `response_model` and `status_code` for a *path operation*.

That defines the metadata about the main response of a *path operation*.

You can also declare additional responses with their models, status codes, etc.

///

/// tip

To declare File bodies, you need to use `File`, because otherwise the parameters would be interpreted as query parameters or body (JSON) parameters.

///

The files will be uploaded as "form data".

/// note | Nota

Isso é suportado desde o FastAPI versão `0.115.0`. 🤓

///

## Parâmetros de Consulta com um Modelo Pydantic { #query-parameters-with-a-pydantic-model }

Declare os **parâmetros de consulta** que você precisa em um **modelo Pydantic**, e então declare o parâmetro como `Query`:

{* ../../docs_src/query_param_models/tutorial001_an_py310.py hl[9:13,17] *}

## Importe `Header` { #import-header }

Primeiro importe `Header`:

{* ../../docs_src/header_params/tutorial001_an_py310.py hl[3] *}

## Declare parâmetros de `Header` { #declare-header-parameters }

Então declare os paramêtros de cabeçalho usando a mesma estrutura que em `Path`, `Query` e `Cookie`.

O primeiro valor é o valor padrão, você pode passar todas as validações adicionais ou parâmetros de anotação:

But you still want to be able to filter and convert the data you return with a `response_model`.

For those cases, you can use a `Response` parameter.

## Use a `Response` parameter { #use-a-response-parameter }

You can declare a parameter of type `Response` in your *path operation function* (as you can do for cookies and headers).

And then you can set the `status_code` in that *temporal* response object.

///

### Import `Depends` { #import-depends }

{* ../../docs_src/dependencies/tutorial001_an_py310.py hl[3] *}

### Declare the dependency, in the "dependant" { #declare-the-dependency-in-the-dependant }

The same way you use `Body`, `Query`, etc. with your *path operation function* parameters, use `Depends` with a new parameter:

            assertEquals(1, existsExceptions.length, "exists() should declare CIFSException");
            assertEquals(CIFSException.class, existsExceptions[0], "Should declare CIFSException");
            assertEquals(1, getTypeExceptions.length, "getType() should declare CIFSException");
            assertEquals(CIFSException.class, getTypeExceptions[0], "Should declare CIFSException");
        }

        @Test

Les paramètres de la fonction seront reconnus comme tel :

* Si le paramètre est aussi déclaré dans le **chemin**, il sera utilisé comme paramètre de chemin.
* Si le paramètre est d'un **type singulier** (comme `int`, `float`, `str`, `bool`, etc.), il sera interprété comme un paramètre de **requête**.
* Si le paramètre est déclaré comme ayant pour type un **modèle Pydantic**, il sera interprété comme faisant partie du **corps** de la requête.

/// tip

If you have strict type checks in your editor, mypy, etc, you can declare the function return type as `Any`.

That way you tell the editor that you are intentionally returning anything. But FastAPI will still do the data documentation, validation, filtering, etc. with the `response_model`.

///

### `response_model` Priority { #response-model-priority }

We could do better.

We can declare a `UserBase` model that serves as a base for our other models. And then we can make subclasses of that model that inherit its attributes (type declarations, validation, etc).

All the data conversion, validation, documentation, etc. will still work as normally.