# Windows has a relatively short command line limit, which TF has begun to hit.
# See https://docs.bazel.build/versions/main/windows.html
common:windows --features=compiler_param_file
common:windows --features=archive_param_file

# Speed Windows compile times. Available in VS 16.4 (we are on 16.11). See
# https://groups.google.com/a/tensorflow.org/d/topic/build/SsW98Eo7l3o/discussion

    """
    # assert asyncio.iscoroutinefunction(func), "WebSocket endpoints must be async"

    async def app(scope: Scope, receive: Receive, send: Send) -> None:
        session = WebSocket(scope, receive=receive, send=send)

        async def app(scope: Scope, receive: Receive, send: Send) -> None:
            async with AsyncExitStack() as request_stack:
                scope["fastapi_inner_astack"] = request_stack

    And this path operation will:

    * Send the invoice to the client.
    * Collect the money from the client.
    * Send a notification back to the API user (the external developer), as a callback.
        * At this point is that the API will somehow send a POST request to the
            external API with the notification of the invoice event
            (e.g. "payment successful").
    """

        To be awaitable, compatible with async, this is run in threadpool.
        """
        return await super().read(size)

    async def seek(
        self,
        offset: Annotated[
            int,
            Doc(
                """
                The position in bytes to seek to in the file.
                """
            ),
        ],
    ) -> None:
        """
        Move to a position in the file.

              ...

    ```
    """

    def __init__(
        self,
        status_code: Annotated[
            int,
            Doc(
                """
                HTTP status code to send to the client.
                """
            ),
        ],
        detail: Annotated[
            Any,
            Doc(
                """

    * With <a href="https://github.com/ciscorn/starlette-graphene3" class="external-link" target="_blank">starlette-graphene3</a>

## GraphQL with Strawberry { #graphql-with-strawberry }

This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.

/// info

Keep in mind that dataclasses can't do everything Pydantic models can do.

So, you might still need to use Pydantic models.

But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

///

# Initialize the TensorFlow repository and all dependencies.
#
# The cascade of load() statements and tf_workspace?() calls works around the
# restriction that load() statements need to be at the top of .bzl files.
# E.g. we can not retrieve a new repository with http_archive and then load()
# a macro from that repository in the same file.
load("@//tensorflow:workspace3.bzl", "tf_workspace3")

        ),
    ] = None,
    include_in_schema: Annotated[
        bool,
        Doc(
            """
            To include (or not) this parameter field in the generated OpenAPI.
            You probably don't need it, but it's available.

            This affects the generated OpenAPI (e.g. visible at `/docs`).
            """
        ),
    ] = True,
    json_schema_extra: Annotated[
        Union[dict[str, Any], None],