New RunLLM response generated: >>>*# Question* 👋 when using

pyflyte serialize workflows

is it possible to constrain its memory utilization? we're seeing this OOM quite frequently # Answer The

pyflyte serialize workflows

command does not have built-in options to directly constrain memory utilization. However, you can manage memory usage by adjusting the task resource limits in your Flyte configuration. According to GitHub Issue #2376, setting appropriate memory limits for tasks can help prevent OOM errors. Example:

from flytekit import task, workflow, Resources

@task(limits=Resources(mem="500Mi"))
def my_task():
    # Task implementation

@workflow
def my_workflow():
    my_task()

Would you like more detail on configuring task resources or other potential solutions? Sources: - GitHub Issue #2376 Slack Link https://flyte-org.slack.com/archives/CP2HDHKE1/p1718668128.115289 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.