Hello @Marvin, when I attempt to send a task to a taskRunner such as ray in prefect, I get the following:

@flow(
    task_runner=RayTaskRunner(
        address="<http://raycluster-kuberay-1-head-svc.kuberay.svc.cluster.local:6379>",
    )
)

File "/usr/local/lib/python3.11/site-packages/ray/client_builder.py", line 344, in _get_builder_from_address
    assert "ClientBuilder" in dir(
           ^^^^^^^^^^^^^^^^^^^^^^^
AssertionError: Module: http does not have ClientBuilder.

It seems like you're encountering an issue related to using Ray as a

TaskRunner

in Prefect. The error you're seeing,

AssertionError: Module: http does not have ClientBuilder,

, suggests there might be a problem with the way the Ray client is being connected or configured. Here are some steps and considerations to troubleshoot this: 1. Installation and Import: Make sure you've installed the

prefect-ray

package correctly to use the

RayTaskRunner

. You can do this with

pip install -U prefect-ray

. Also, ensure that you're importing

RayTaskRunner

correctly from

prefect_ray.task_runners

. 2. Configuration: Check the way you're configuring the Ray address. It's essential to ensure that the address you're using for Ray is correct and that the Ray cluster is accessible from your current environment. 3. Ray Compatibility: The issue might also be due to a mismatch or incompatibility between the versions of Prefect, Ray, and any specific configurations they require. You might want to check the compatibility matrix or documentation for any known issues. You might find more detailed information on configuring Ray in Prefect's guide on task runners. Unfortunately, no specific GitHub issues have been found to provide further insight into this problem. If you've ensured the above points are correctly set and the issue persists, consider reaching out to the community or checking if other users have similar issues. Remember, even the universe is sometimes more complex than we'd like—just like getting Ray and Prefect to cooperate smoothly.

@Marvin if I am using prefect 2.19.3 with prefect ray, How do I pass the container that the job is supposed to use to the rayTaskRunner?

Configuring a specific container to use with the

RayTaskRunner

in Prefect can be a bit nuanced since it's tied to how your Ray cluster is set up rather than directly through Prefect. From the documentation and guides, here are some steps you can consider: 1. Ray Cluster Configuration: - The containerization aspect is usually managed by the Ray cluster setup itself. If you're using Ray on Kubernetes or any similar orchestration tool, you'll specify the container details in the Ray cluster configuration. - Make sure your Ray cluster is configured to use the desired container images for the worker nodes. 2. Prefect Configuration: - When you define a flow with

RayTaskRunner

, you're essentially telling Prefect to submit tasks to an already existing Ray cluster. Prefect doesn't directly manage the container specifications; it utilizes the configuration that Ray has set up. Here's a useful link to Prefect's guide on using Ray with Prefect, which might give you additional insights or configurations for your setup. If you're still encountering issues or need to adapt your Prefect setup further, you might need to delve into Ray's configuration settings directly. Consider reaching out to Ray's community or documentation for specific container management under a Ray deployment. Ah, the joys of containers and clusters—it's like trying to find a cup holder in Marvin's head. Complex, but doable! 😊