ml_models = {}


@asynccontextmanager
async def lifespan(app: FastAPI):
    # Load the ML model
    ml_models["answer_to_everything"] = fake_answer_to_everything_ml_model
    yield
    # Clean up the ML models and release the resources
    ml_models.clear()


app = FastAPI(lifespan=lifespan)


@app.get("/predict")
async def predict(x: float):
    result = ml_models["answer_to_everything"](x)

  TensorFlow's `tf-nightly` package will soon be updated to TensorFlow 2.0.

  Please upgrade your code to TensorFlow 2.0:
    * https://www.tensorflow.org/guide/migrate

  Or install the latest stable TensorFlow 1.X release:
    * `pip install -U "tensorflow==1.*"`

  Otherwise your code may be broken by the change.

  """)

# Make sure directory containing top level submodules is in

) -> Callable[[WebSocket], Coroutine[Any, Any, Any]]:
    async def app(websocket: WebSocket) -> None:
        async with AsyncExitStack() as async_exit_stack:
            # TODO: remove this scope later, after a few releases
            # This scope fastapi_astack is no longer used by FastAPI, kept for
            # compatibility, just in case
            websocket.scope["fastapi_astack"] = async_exit_stack

from mkdocs.structure.files import File, Files
from mkdocs.structure.nav import Link, Navigation, Section
from mkdocs.structure.pages import Page

non_traslated_sections = [
    "reference/",
    "release-notes.md",
]


@lru_cache
def get_missing_translation_content(docs_dir: str) -> str:
    docs_dir_path = Path(docs_dir)
    missing_translation_path = docs_dir_path.parent.parent / "missing-translation.md"

  curr_version_int = convert_version_to_int(curr_version)

  # Check if current bazel version can be detected properly.
  if not curr_version_int:
    print('WARNING: current bazel installation is not a release version.')
    return curr_version

  print('You have bazel %s installed.' % curr_version)
  return curr_version


def set_cc_opt_flags(environ_cp):
  """Set up architecture-dependent optimization flags.