E um retorno com o código de status `200` que utiliza o seu `response_model`, porém inclui um `example` customizado:

```Python hl_lines="20-31"
{!../../docs_src/additional_responses/tutorial003.py!}
```

Isso será combinado e incluído em seu OpenAPI, e disponibilizado na documentação da sua API:

<img src="/img/tutorial/additional-responses/image01.png">

## Combinar retornos predefinidos e personalizados

 *
 * This is because the ModelProcessor interface extends ModelLocator and ModelReader. If we
 * made this component available under all its interfaces then it could end up being injected
 * into itself leading to a stack overflow.
 *
 * A side effect of using @Typed is that it translates to explicit bindings in the container.
 * So instead of binding the component under a 'wildcard' key it is now bound with an explicit

        options.addOption(Option.builder(Character.toString(NON_RECURSIVE))
                .longOpt("non-recursive")
                .desc(
                        "Do not recurse into sub-projects. When used together with -pl, do not recurse into sub-projects of selected aggregators")
                .build());
        options.addOption(Option.builder(Character.toString(UPDATE_SNAPSHOTS))
                .longOpt("update-snapshots")

```Python hl_lines="3  6-8"
{!../../docs_src/sub_applications/tutorial001.py!}
```

### Unteranwendung

Erstellen Sie dann Ihre Unteranwendung und deren *Pfadoperationen*.

Diese Unteranwendung ist nur eine weitere Standard-FastAPI-Anwendung, aber diese wird „gemountet“:

```Python hl_lines="11  14-16"
{!../../docs_src/sub_applications/tutorial001.py!}
```

### Die Unteranwendung mounten

              @Override
              protected void finalize() {
                finalizerRan.countDown();
              }
            });

    // Don't copy this into your own test!
    // Use e.g. awaitClear or await(CountDownLatch) instead.
    GcFinalization.awaitFullGc();

    // If this test turns out to be flaky, add a second call to awaitFullGc()

# "pip tests" run a similar suite of tests the "nonpip" tests, but do something
# odd to attempt to validate the quality of the pip package. The wheel is
# installed into a virtual environment, and then that venv is used to run all
# bazel tests with a special flag "--define=no_tensorflow_py_deps=true", which
# drops all the bazel dependencies for each py_test; this makes all the tests

`tf` instead of `tensorflow`, following the common practice of importing
TensorFlow via the command `import tensorflow as tf`.

The primary function of this module is to import all of the public TensorFlow
interfaces into a single place. The interfaces themselves are located in
sub-modules, as described below.

Note that the file `__init__.py` in the TensorFlow source code tree is actually

   *       CompactHashing.createTable, whose values are either
   *       <ul>
   *         <li>UNSET, meaning "null pointer"
   *         <li>one plus an index into the entries and elements array
   *       </ul>
   *   <li>another java.util.Set delegate implementation. In most modern JDKs, normal java.util hash

  // `handSize` is a small positive number that configures the
  // shuffle sharding of requests into queues.  When enqueuing a request
  // at this priority level the request's flow identifier (a string
  // pair) is hashed and the hash value is used to shuffle the list
  // of queues and deal a hand of the size specified here.  The
  // request is put into one of the shortest queues in that hand.

          // Defeat branch predictor for: c < 0x80 ; branch taken 50% of the time.
          return 0x100;
        } else if (userFriendly.matches("(?i)(?:Greek|Cyrillic|European|ISO.?8859)")) {
          // Mostly 2-byte UTF-8 sequences - "European" text
          return 0x800;
        } else if (userFriendly.matches("(?i)(?:Chinese|Han|Asian|BMP)")) {
          // Mostly 3-byte UTF-8 sequences - "Asian" text