* return null; // Didn't find a preemptive auth scheme.
 * ```
 *
 * ## Reactive Authentication
 *
 * Implementations authenticate by returning a follow-up request that includes an authorization
 * header, or they may decline the challenge by returning null. In this case the unauthenticated
 * response will be returned to the caller that triggered it.
 *
 * Implementations should check if the initial request already included an attempt to

   *
   * In order to support preemptive authentication we pass a fake "Auth Failed" response to the
   * authenticator. This gives the authenticator the option to customize the CONNECT request. It can
   * decline to do so by returning null, in which case OkHttp will use it as-is.
   */
  @Throws(IOException::class)
  private fun createTunnelRequest(route: Route): Request {
    val proxyConnectRequest =
      Request

For example, you could decide to read and validate the request with your own code, without using the automatic features of FastAPI with Pydantic, but you could still want to define the request in the OpenAPI schema.

You could do that with `openapi_extra`:

{* ../../docs_src/path_operation_advanced_configuration/tutorial006.py hl[19:36, 39:40] *}

## Singular values in body { #singular-values-in-body }

The same way there is a `Query` and `Path` to define extra data for query and path parameters, **FastAPI** provides an equivalent `Body`.

For example, extending the previous model, you could decide that you want to have another key `importance` in the same body, besides the `item` and `user`.

If you declare it as is, because it is a singular value, **FastAPI** will assume that it is a query parameter.

You can define Header parameters the same way you define `Query`, `Path` and `Cookie` parameters.

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

First import `Header`:

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

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

Then declare the header parameters using the same structure as with `Path`, `Query` and `Cookie`.

## Define `File` and `Form` parameters { #define-file-and-form-parameters }

Create file and form parameters the same way you would for `Body` or `Query`:

{* ../../docs_src/request_forms_and_files/tutorial001_an_py39.py hl[10:12] *}

The files and form fields will be uploaded as form data and you will receive the files and form fields.

And you can declare some of the files as `bytes` and some as `UploadFile`.

Each attribute of a Pydantic model has a type.

But that type can itself be another Pydantic model.

So, you can declare deeply nested JSON "objects" with specific attribute names, types and validations.

All that, arbitrarily nested.

### Define a submodel { #define-a-submodel }

For example, we can define an `Image` model:

{* ../../docs_src/body_nested_models/tutorial004_py310.py hl[7:9] *}

You can define Cookie parameters the same way you define `Query` and `Path` parameters.

## Import `Cookie` { #import-cookie }

First import `Cookie`:

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

## Declare `Cookie` parameters { #declare-cookie-parameters }

Then declare the cookie parameters using the same structure as with `Path` and `Query`.

With `Form` you can declare the same configurations as with `Body` (and `Query`, `Path`, `Cookie`), including validation, examples, an alias (e.g. `user-name` instead of `username`), etc.

/// info

`Form` is a class that inherits directly from `Body`.

///

/// tip

///

/// 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".