@app.get("/no_response_model-annotation-return_same_model")
def no_response_model_annotation_return_same_model() -> User:
    return User(name="John", surname="Doe")


@app.get("/no_response_model-annotation-return_exact_dict")
def no_response_model_annotation_return_exact_dict() -> User:
    return {"name": "John", "surname": "Doe"}


@app.get("/no_response_model-annotation-return_invalid_dict")

        or is_dataclass(annotation)
    )


def field_annotation_is_complex(annotation: Union[type[Any], None]) -> bool:
    origin = get_origin(annotation)
    if origin is Union or origin is UnionType:
        return any(field_annotation_is_complex(arg) for arg in get_args(annotation))

    if origin is Annotated:
        return field_annotation_is_complex(get_args(annotation)[0])

    return (

            default=param.default,
            annotation=get_typed_annotation(param.annotation, globalns),
        )
        for param in signature.parameters.values()
    ]
    typed_signature = inspect.Signature(typed_params)
    return typed_signature


def get_typed_annotation(annotation: Any, globalns: dict[str, Any]) -> Any:
    if isinstance(annotation, str):
        annotation = ForwardRef(annotation)

            serialization_alias = alias
        if validation_alias in (_Unset, None):
            validation_alias = alias
        kwargs.update(
            {
                "annotation": annotation,
                "alias_priority": alias_priority,
                "validation_alias": validation_alias,
                "serialization_alias": serialization_alias,
                "strict": strict,

def copy_field_info(*, field_info: FieldInfo, annotation: Any) -> FieldInfo:
    cls = type(field_info)
    merged_field_info = cls.from_annotation(annotation)
    new_field_info = copy(field_info)
    new_field_info.metadata = merged_field_info.metadata
    new_field_info.annotation = merged_field_info.annotation
    return new_field_info

from pydantic.fields import FieldInfo

from .utils import needs_py310


def test_model_field_default_required():
    from fastapi._compat import v2

    # For coverage
    field_info = FieldInfo(annotation=str)
    field = v2.ModelField(name="foo", field_info=field_info)
    assert field.default is Undefined


def test_complex():
    app = FastAPI()

    @app.post("/")
    def foo(foo: Union[str, list[int]]):

_invalid_args_message = (
    "Invalid args for response field! Hint: "
    "check that {type_} is a valid Pydantic field type. "
    "If you are using a return type annotation that is not a valid Pydantic "
    "field (e.g. Union[Response, dict, None]) you can disable generating the "
    "response model from the type annotation with the path operation decorator "
    "parameter response_model=None. Read more: "
    "https://fastapi.tiangolo.com/tutorial/response-model/"
)

7. Here the `response_model` is using a type annotation of a list of `Author` dataclasses.

    Again, you can combine `dataclasses` with standard type annotations.

8. Notice that this *path operation function* uses regular `def` instead of `async def`.

    As always, in FastAPI you can combine `def` and `async def` as needed.

Example:

    Source (English):

        «««
        ## Type hints and annotations { #type-hints-and-annotations }
        »»»

    Translate with (German) – notice the hyphen:

        «««
        ## Typhinweise und -annotationen { #type-hints-and-annotations }
        »»»

    Do NOT translate with (German) – notice the dash:

        «««

## 0.89.1

### Fixes

* 🐛 Ignore Response classes on return annotation. PR [#5855](https://github.com/tiangolo/fastapi/pull/5855) by [@Kludex](https://github.com/Kludex). See the new docs in the PR below.

### Docs