AgitatedDove14 permanent. I want to start with a CLI interface that allows me add users to the trains server

CostlyOstrich36

😶‍🌫️

So just to be clear - the file server has nothing to do with the storage?

I tried what you said in the previous response, setting sdk.aws.s3.key and sdk.aws.s3.secret to the ones in my MINIO. Yet when I try to download an object, i get the following
` >>> result = manager.get_local_copy(remote_url="s3://*******:9000/test-bucket/test.txt")
2020-10-15 13:24:45,023 - trains.storage - ERROR - Could not download s3://*****:9000/test-bucket/test.txt , err: SSL validation failed for https://*****:9000/test-bucket/test.txt [SSL: WRONG_VERSION_NU...

Okay Jake, so that basically means I don't have to touch any server configuration regarding the file-server on the trains server. It will simply get ignored and all I/O initiated by clients with the right configuration will cover for that?

I just tried setting the conf in the section Martin said, it works perfectly

Okay martin, I'll try that

Martin: In your trains.conf, change the value
files_server: ' s3://ip :port/bucket'

Isn't this a client configuration ( trains-init )? Shouldn't be any change to the server configuration ( /opt/trains/config... )?

I know I can configure the file server on trains-init - but that only touches the client side, what about the container on the trains server?

To be clearer - how to I refrain from using the built in file-server altogether - and use MINIO for any storage need?

Thia is just keeping getting better and better.... 🤩

I think I got it, I'll ping her again if it won't succeed

So could you re-explain assuming my piepline object is created by pipeline = PipelineController(...) ?

AgitatedDove14

So nope, this doesn't solve my case, I'll explain the full use case from the beginning.

I have a pipeline controller task, which launches 30 tasks. Semantically there are 10 applications, and I run 3 tasks for each (those 3 are sequential, so in the UI it looks like 10 lines of 3 tasks).

In one of those 3 tasks that run for every app, I save a dataframe under the name "my_dataframe".
What I want to achieve is once all tasks are over, to collect all those "my_dataframe" arti...

and then how would I register the final artifact to the pipelien? AgitatedDove14 ⬆

I want to collect the dataframes from teh red tasks, and display them in the pipeline task

Okay, looks interesting but actually there is no final task, this is the pipeline layout

few minutes and I'll look at it

AgitatedDove14 worked like a charm, thanks a lot!

I'm trying it now

Sorry.. I still don't get it - when I'm launching an agent with the --docker flag or with the --services-mode flag, what is the difference? Can I use both flags? what does it mean? 🤔

I need code access, not UI access

I don't think the problem is setting that variable, I think it has something to do with it but not that obvious... Because it did work for me in the past, since then we docker-compose up/downed a few times, changed some other things etc... Can't figure out what made it get to this point

I re-executed the experiemnt, nothing changes

it is a model name

Thanks 🙂

I guess what I want is a way to define environment variables in agents

SuccessfulKoala55 :shrug:

I followed the upgrading still nothing