return {
            "value": req.value or None,
            "embedded_value": req.embedded_model.value or None,
        }

    client = TestClient(app)

    response = client.post("/", json={})
    assert response.status_code == 200, response.text
    assert response.json() == {
        "value": None,
        "embedded_value": None,
    }

    response2 = client.post(

            "Example One": {
                "summary": "Example One Summary",
                "description": "Example One Description",
                "value": {"data": "Data in Body examples, example1"},
            },
            "Example Two": {
                "value": {"data": "Data in Body examples, example2"},
            },
        },
    ),
):
    return item


@app.get("/path_examples/{item_id}")

def test_decimal_encoder_float():
    data = {"value": Decimal(1.23)}
    assert jsonable_encoder(data) == {"value": 1.23}


def test_decimal_encoder_int():
    data = {"value": Decimal(2)}
    assert jsonable_encoder(data) == {"value": 2}


def test_decimal_encoder_nan():
    data = {"value": Decimal("NaN")}
    assert isnan(jsonable_encoder(data)["value"])


def test_decimal_encoder_infinity():

        Doc(
            """
            Default value if the parameter field is not set.
            """
        ),
    ] = Undefined,
    *,
    default_factory: Annotated[
        Union[Callable[[], Any], None],
        Doc(
            """
            A callable to generate the default value.

            This doesn't affect `Path` parameters as the value is always required.

    It's used internally to recognize when a default value has been overwritten, even
    if the overridden default value was truthy.
    """

    def __init__(self, value: Any):
        self.value = value

    def __bool__(self) -> bool:
        return bool(self.value)

    def __eq__(self, o: object) -> bool:
        return isinstance(o, DefaultPlaceholder) and o.value == self.value


DefaultType = TypeVar("DefaultType")

            continue
        if isinstance(value, dict):
            new_schema[key] = _replace_refs(
                schema=value,
                old_name_to_new_name_map=old_name_to_new_name_map,
            )
        elif isinstance(value, list):
            new_value = []
            for item in value:
                if isinstance(item, dict):
                    new_item = _replace_refs(

            "schemas": {
                "Item": {
                    "title": "Item",
                    "required": ["id", "value"],
                    "type": "object",
                    "properties": {
                        "id": {"title": "Id", "type": "string"},
                        "value": {"title": "Value", "type": "string"},
                    },
                },
                "ValidationError": {

            "schemas": {
                "Item": {
                    "title": "Item",
                    "required": ["id", "value"],
                    "type": "object",
                    "properties": {
                        "id": {"title": "Id", "type": "string"},
                        "value": {"title": "Value", "type": "string"},
                    },
                },
                "ValidationError": {

            value, even when they were explicitly set.
            """
        ),
    ] = False,
    exclude_none: Annotated[
        bool,
        Doc(
            """
            Pydantic's `exclude_none` parameter, passed to Pydantic models to define
            if it should exclude from the output any fields that have a `None` value.
            """
        ),
    ] = False,

                                        "value": {"name": "Bar", "price": "35.4"},
                                    },
                                    "invalid": {
                                        "summary": "Invalid data is rejected with an error",
                                        "value": {
                                            "name": "Baz",