"""
        ),
    ] = False,
    media_type: Annotated[
        str,
        Doc(
            """
            The media type of this parameter field. Changing it would affect the
            generated OpenAPI, but currently it doesn't affect the parsing of the data.
            """
        ),
    ] = "application/json",
    alias: Annotated[
        Optional[str],

@needs_py39
def test_incorrect_token(client: TestClient):
    response = client.get("/users/me", headers={"Authorization": "Bearer nonexistent"})
    assert response.status_code == 401, response.text
    assert response.json() == {"detail": "Could not validate credentials"}
    assert response.headers["WWW-Authenticate"] == 'Bearer scope="me"'


@needs_py39
def test_incorrect_token_type(client: TestClient):
    response = client.get(

    return encoded_jwt


async def get_current_user(token: Annotated[str, Depends(oauth2_scheme)]):
    credentials_exception = HTTPException(
        status_code=status.HTTP_401_UNAUTHORIZED,
        detail="Could not validate credentials",
        headers={"WWW-Authenticate": "Bearer"},
    )
    try:
        payload = jwt.decode(token, SECRET_KEY, algorithms=[ALGORITHM])
        username: str = payload.get("sub")

    else:
        authenticate_value = "Bearer"
    credentials_exception = HTTPException(
        status_code=status.HTTP_401_UNAUTHORIZED,
        detail="Could not validate credentials",
        headers={"WWW-Authenticate": authenticate_value},
    )
    try:
        payload = jwt.decode(token, SECRET_KEY, algorithms=[ALGORITHM])
        username: str = payload.get("sub")

    # Normally only one language, but still
    for lang in langs:
        if lang not in lang_to_discussion_map:
            log_message = f"Could not find discussion for language: {lang}"
            logging.error(log_message)
            raise RuntimeError(log_message)
        discussion = lang_to_discussion_map[lang]
        logging.info(

def test_events():
    assert not ml_models, "ml_models should be empty"
    with TestClient(app) as client:
        assert ml_models["answer_to_everything"] == fake_answer_to_everything_ml_model
        response = client.get("/predict", params={"x": 2})
        assert response.status_code == 200, response.text
        assert response.json() == {"result": 84.0}
    assert not ml_models, "ml_models should be empty"


def test_openapi_schema():

    assert response.json() == IsDict(
        {
            "detail": [
                {
                    "type": "greater_than",
                    "loc": ["body", 0, "age"],
                    "msg": "Input should be greater than 0",
                    "input": -1.0,
                    "ctx": {"gt": 0},
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {

    ), "overridden configs should be preserved"
    assert (
        '"deepLinking": true' not in response.text
    ), "overridden configs should not include the old value"
    assert (
        '"syntaxHighlight": false' not in response.text
    ), "not used parameters should not be included"
    assert (
        '"dom_id": "#swagger-ui"' in response.text
    ), "default configs should be preserved"

                    "loc": ["query", "q", 0],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "five",
                },
                {
                    "type": "int_parsing",
                    "loc": ["query", "q", 1],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "six",

class APIKeyBase(SecurityBase):
    pass


class APIKeyQuery(APIKeyBase):
    """
    API key authentication using a query parameter.

    This defines the name of the query parameter that should be provided in the request
    with the API key and integrates that into the OpenAPI documentation. It extracts
    the key value sent in the query parameter automatically and provides it as the