return name

    async def get_model_c() -> ModelC:
        return ModelC(username="test-user", password="test-password")

    @app.get("/model/{name}", response_model=ModelA)
    async def get_model_a(name: str, model_c=Depends(get_model_c)):
        return {"name": name, "description": "model-a-desc", "foo": model_c}

    client = TestClient(app)
    return client


@needs_pydanticv2

            "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/"
        ) from None


def create_cloned_field(
    field: ModelField,
    *,

            "content": {"application/x-yaml": {"schema": Item.model_json_schema()}},
            "required": True,
        },
    },
)
async def create_item(request: Request):
    raw_body = await request.body()
    try:
        data = yaml.safe_load(raw_body)
    except yaml.YAMLError:
        raise HTTPException(status_code=422, detail="Invalid YAML")
    try:
        item = Item.model_validate(data)
    except ValidationError as e:

    def __init__(
        self,
        *,
        scheme: str,
        scheme_name: Optional[str] = None,
        description: Optional[str] = None,
        auto_error: bool = True,
    ):
        self.model = HTTPBaseModel(scheme=scheme, description=description)
        self.scheme_name = scheme_name or self.__class__.__name__
        self.auto_error = auto_error

    async def __call__(
        self, request: Request

    assert response.status_code == 422, response.text
    assert response.json() == IsDict(
        {
            "detail": [
                {
                    "type": "model_attributes_type",
                    "loc": ["body"],
                    "msg": "Input should be a valid dictionary or object to extract fields from",
                    "input": "name=Foo&price=50.5",
                }

    assert response.status_code == 422, response.text
    assert response.json() == IsDict(
        {
            "detail": [
                {
                    "type": "model_attributes_type",
                    "loc": ["body"],
                    "msg": "Input should be a valid dictionary or object to extract fields from",
                    "input": "name=Foo&price=50.5",
                }

def test_encode_model_with_alias_raises():
    with pytest.raises(ValidationError):
        ModelWithAlias(foo="Bar")


def test_encode_model_with_alias():
    model = ModelWithAlias(Foo="Bar")
    assert jsonable_encoder(model) == {"Foo": "Bar"}


def test_encode_model_with_default():
    model = ModelWithDefault(foo="foo", bar="bar")

    all_fields = get_fields_from_routes(list(routes or []) + list(webhooks or []))
    model_name_map = get_compat_model_name_map(all_fields)
    schema_generator = GenerateJsonSchema(ref_template=REF_TEMPLATE)
    field_mapping, definitions = get_definitions(
        fields=all_fields,
        schema_generator=schema_generator,
        model_name_map=model_name_map,
        separate_input_output_schemas=separate_input_output_schemas,
    )

                provided in one of multiple optional ways (for example, in a query
                parameter or in an HTTP Bearer token).
                """
            ),
        ] = True,
    ):
        self.model: APIKey = APIKey(
            **{"in": APIKeyIn.query},  # type: ignore[arg-type]
            name=name,
            description=description,
        )
        self.scheme_name = scheme_name or self.__class__.__name__

    def _model_rebuild(model: Type[BaseModel]) -> None:
        model.model_rebuild()

    def _model_dump(
        model: BaseModel, mode: Literal["json", "python"] = "json", **kwargs: Any
    ) -> Any:
        return model.model_dump(mode=mode, **kwargs)

    def _get_model_config(model: BaseModel) -> Any:
        return model.model_config

    def get_schema_from_model_field(