///

## OpenAPI and API docs { #openapi-and-api-docs }

If you return additional status codes and responses directly, they won't be included in the OpenAPI schema (the API docs), because FastAPI doesn't have a way to know beforehand what you are going to return.

### Embedding a Java runtime in the Gradle distribution

There have been discussions on embedding a Java runtime in the Gradle distribution.
This would allow users to run Gradle without having to install a Java runtime beforehand.
This capability could help increase Gradle adoption outside of the JVM ecosystem.

Gradle can be invoked in different ways:
* Through the [Gradle Wrapper](https://docs.gradle.org/8.8/userguide/gradle_wrapper.html)

## Bodies of arbitrary `dict`s { #bodies-of-arbitrary-dicts }

You can also declare a body as a `dict` with keys of some type and values of some other type.

This way, you don't have to know beforehand what the valid field/attribute names are (as would be the case with Pydantic models).

This would be useful if you want to receive keys that you don't already know.

---

This is useful if you don't know the valid field/attribute names (that would be needed for a Pydantic model) beforehand.

In this case, you can use `dict`:

{* ../../docs_src/extra_models/tutorial005_py310.py hl[6] *}

## Recap { #recap }

Use multiple Pydantic models and inherit freely for each case.

        final LocalDateTime beforeAdd = session.getLastAccessedAt();

        final ChatMessage message = ChatMessage.userMessage("Hello");
        session.addMessage(message);

        assertEquals(1, session.getMessages().size());
        assertEquals("Hello", session.getMessages().get(0).getContent());
        assertTrue(session.getLastAccessedAt().isAfter(beforeAdd) || session.getLastAccessedAt().isEqual(beforeAdd));
    }

*   Hot-fix was needed for an issue affecting the TensorFlow installation
    process.
    *   TensorFlow 2.15.0 Python package was requesting `tensorrt`-related
        packages that cannot be found unless the user installs them beforehand
        or provides additional installation flags.
    *   This dependency affected anyone installing TensorFlow 2.15 alongside
        NVIDIA CUDA dependencies via `pip install tensorflow[and-cuda]`.