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Integrate with DagsHub's MLflow API #35
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Hello @math4mad. That's not the way to authenticate into an # "credentials" is a base64-encoded string
credentials = "<your_username>:<your_password>"
MLFlow(<your_base_uri>; headers=Dict("Authorization" => "Basic $credentials")) This is an ugly way to send authorizations. I'm going to make it pretty. However, you can't use this package because it is supporting the modern |
This last change is using the generic Notes:
I'm thinking about improving the way we are defining credentials:
## Old way
using Base64
using MLFlowClient
credentials = base64encode("missy:gala")
MLFlow("http://localhost:5000"; headers=Dict("Authorization"=>"Basic $credentials"))
## New way
using MLFlowClient
MLFlow("http://localhost:5000"; auth=("username"=>"missy", "password"=>"gala")) |
Thanks @pebeto for taking the lead here. Your suggestion sounds reasonable to me, but would be good to get @deyandyankov's view. Are you adding Instead of |
@deyandyankov Can you please comment on @pebeto's proposal? |
I think having both |
at now still can't work with remote url of dagshub. could give me a hint? |
According with this part
dagshub mlflow integrations
how to fill params of headers
follow Set-up your credentials setting name and token , now it not working
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