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Kserve dependencies conflicts with KFP - Tensorflow - etc...
See original GitHub issue/kind feature
Describe the solution you’d like
Hi kserve team, I have been trying to install kserve on python with other libraries but this seems to be an impossible task due to dependencies conflicts. Kserve0.8.0 had some old libraries like numpy that don’t get along with tensorflow. I was hoping this problem would be fixed with kserve0.9.0 which actually happened and many dependencies were updated to a newer version, but those versions are now set to a new and pinned that won’t work with other libraries like kfp because of kubernetes dependency
Is there a possibility to have dependencies requirements that can match other famous libraries requirements such as
tensorflow&kfpetc…?
Anything else you would like to add: [Miscellaneous information that will assist in solving the issue.]
Issue Analytics
- State:
- Created a year ago
- Reactions:1
- Comments:9 (9 by maintainers)
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@safoinme
It would be great if you could create a PR for this! 👍 You can add myself and @yuzisun as reviewers
I think that will be okay too.
I think Kubeflow is currently trying to upgrade everything to Kubernetes 1.22 for the next release.
It seems KFP is focusing on v2 SDK so haven’t updated the v1 SDK to allow/support new K8s versions.