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ModelName requirement in API calls

See original GitHub issue

When creating KFservers such as xgboost the modelName is taken to be metdata.Name. The user then needs to specify this twice in an API call. For example, in the xgboost sample:

MODEL_NAME=xgboost-iris
curl -v -H "Host: xgboost-iris.default.svc.cluster.local" http://$CLUSTER_IP/models/$MODEL_NAME:predict -d $INPUT_PATH

Should we keep this requirement or allow users to just curl their endpoint and behind the scenes add the modelName to the path as we route the request?, e.g.

curl -v -H "Host: xgboost-iris.default.svc.cluster.local" http://$CLUSTER_IP/predict

If users can specify the modelName then they could try other model names that might happen to be loaded on that server which maybe not what we want.

Issue Analytics

State:
Created 4 years ago
Comments:8 (3 by maintainers)

Top GitHub Comments

1reaction

cliveseldoncommented, Jun 10, 2019

Seldon does specify paths like /api/v0.1/predictions but for the kfserver implementation we have conformed to the tensorflow paths that allow model specification.

As the executor is optional I assume an istio VirtualService is best?

0reactions

jtfogartycommented, Jan 15, 2020

/kind feature /priority p2

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