cls, source: Type[Any], handler: Callable[[Any], CoreSchema]
    ) -> CoreSchema:
        return with_info_plain_validator_function(cls._validate)


class DefaultPlaceholder:
    """
    You shouldn't use this class directly.

    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):

            if it should exclude from the output the fields that had the same default
            value, even when they were explicitly set.
            """
        ),
    ] = False,
    exclude_none: Annotated[
        bool,
        Doc(
            """
            Pydantic's `exclude_none` parameter, passed to Pydantic models to define

    ), "syntaxHighlight should be included and converted to JSON"
    assert (
        '"dom_id": "#swagger-ui"' in response.text
    ), "default configs should be preserved"
    assert "presets: [" in response.text, "default configs should be preserved"
    assert (
        "SwaggerUIBundle.presets.apis," in response.text
    ), "default configs should be preserved"
    assert (

client = TestClient(app)


def test_dependency_contextvars():
    """
    Check that custom middlewares don't affect the contextvar context for dependencies.

    The code before yield and the code after yield should be run in the same contextvar
    context, so that request_state_context_var.reset(contextvar_token).

    If they are run in a different context, that raises an error.
    """
    response = client.get("/user")

    assert response.json() == IsDict(
        {
            "detail": [
                {
                    "type": "enum",
                    "loc": ["path", "model_name"],
                    "msg": "Input should be 'alexnet', 'resnet' or 'lenet'",
                    "input": "foo",
                    "ctx": {"expected": "'alexnet', 'resnet' or 'lenet'"},
                }
            ]
        }
    ) | IsDict(

    assert response.json() == IsDict(
        {
            "detail": [
                {
                    "type": "int_parsing",
                    "loc": ["path", "item_id"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "foo",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {

    raise HTTPException(status_code=204)


@app.get("/http-no-body-statuscode-with-detail-exception")
async def no_body_status_code_with_detail_exception():
    raise HTTPException(status_code=204, detail="I should just disappear!")


@app.get("/starlette-items/{item_id}")
async def read_starlette_item(item_id: str):
    if item_id not in items:
        raise StarletteHTTPException(status_code=404, detail="Item not found")

        {
            "detail": [
                {
                    "type": "string_pattern_mismatch",
                    "loc": ["body", "grant_type"],
                    "msg": "String should match pattern 'password'",
                    "input": "incorrect",
                    "ctx": {"pattern": "password"},
                }
            ]
        }
    ) | IsDict(

    importlib.import_module("tf_keras.src.optimizers")
  else:
    importlib.import_module("keras.src.optimizers")
except (ImportError, AttributeError):
  pass

del importlib

# Delete modules that should be hidden from dir().
# Don't fail if these modules are not available.
# For e.g. this file will be originally placed under tensorflow/_api/v1 which
# does not have "python", "core" directories. Then, it will be copied

                ],
            ),
        ):
            return item

    # TODO: enable these tests once/if Form(embed=False) is supported
    # TODO: In that case, define if File() should support example/examples too
    # @app.post("/form_example")
    # def form_example(firstname: str = Form(example="John")):
    #     return firstname

    # @app.post("/form_examples")
    # def form_examples(