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Hi everyone,
When I try build deployment I get this error:

`RuntimeError: A 'sync_compatible' method was called from a context that was previously async but is now sync. The sync call must be changed to run in a worker thread to support sending the coroutine for 'build_from_flow' to the main thread.`  I followed this guide: <https://docs.prefect.io/tutorials/deployments/#build-a-deployment-definition> Any idea what went wrong? Using prefect 2.3.1 And deployment in scripts looks like this:

```deployment = Deployment.build_from_flow(
    flow=main,
    name="model_training",
    schedule=IntervalSchedule(interval=timedelta(minutes=5)),
    work_queue_name="ml"
)

deployment.apply()```

Hi Yusuf! Could you perhaps try using the prefect deployment CLI? way easier, that way you don't have to worry about sync/async - this guide provides many resources to get started <https://discourse.prefect.io/t/prefect-deployments-faq/1467>

some practical examples: <https://discourse.prefect.io/t/how-to-deploy-all-flows-from-a-project-at-once/1566>

If you want to use the Python Deployment file way <@U03TVBD62A3>, you’re very close. Just pass your interval schedule object to the `schedule` paramater. The work queue name gets passed to `work_queue_name`

You can see a guide I wrote here: <https://medium.com/the-prefect-blog/deploy-prefect-pipelines-with-python-perfect-68c944a3a89f>

Ekran görüntüsü 2022-09-10 21-10-09.png

<@U03KWSKFN8L> Jeff thanks for answering. I can start agent now. But there is another issue which is same issue when I try deployment cli. When I start prefect agent all tasks and flow runs without any error but mlflow artifacts doesn't saves relative path artifacts. I don't think issue was mlflow because I have task which cleans previous mlflow artifacts. That tasks doesn't excute either.
Here is my flow and path task.:

Edit: I can run my script as regular python file and mlflow artifacts saves like expected.

<@U02H1A95XDW> Thanks for pointing deployment cli. apparently I got all wrong. I was trying deployment in python file and deployment cli. I understand now I got two option for deployment. Thanks.

Ahh that's indeed a bit confusing, maybe we can make it clearer in the docs, great that you figured it out!