V1 Microservice has restrictive/conflicting dependencies with common ML frameworks

[mwm5945]

Describe the bug

The V1 python microservice has restrictive dependencies, which can conflict with common ML frameworks when installing them. For example, newer version of tensorflow require flatbuffers>=2.0.0, which directly conflicts with the requirement here:

seldon-core/python/setup.py

Line 29 in f9d3950

"flatbuffers<2.0.0",

. I've also seen issues with URLlib, cryptography, and others. Would it be possible to loosen the requirements a bit here to allow broader packages to be utilized?

To reproduce

$ pip3 install seldon-core==1.16.0 tensorflow==2.12.0
... abbreviated output ...
ERROR: Cannot install seldon-core==1.16.0 and tensorflow-macos==2.13.0rc1 because these package versions have conflicting dependencies.

The conflict is caused by:
    seldon-core 1.16.0 depends on flatbuffers<2.0.0
    tensorflow-macos 2.12.0 depends on flatbuffers>=23.1.21

To fix this you could try to:
1. loosen the range of package versions you've specified
2. remove package versions to allow pip attempt to solve the dependency conflict

ERROR: ResolutionImpossible: for help visit https://pip.pypa.io/en/latest/topics/dependency-resolution/#dealing-with-dependency-conflicts

Expected behaviour

Environment

Model Details

• Images of your model: [Output of: kubectl get seldondeployment -n <yourmodelnamespace> <seldondepname> -o yaml | grep image: where <yourmodelnamespace>]
• Logs of your model: [You can get the logs of your model by running kubectl logs -n <yourmodelnamespace> <seldonpodname> <container>]