• Package: package: azure-ai-ml
• Version: 1.20.0
• OS: Windows
• Python version: 3.11

Describe the bug
In my project I create an environment which build a docker image

ml_client = MLClient(...)
ctx = BuildContext(path=".", dockerfile_path="Dockerfile")
env = Environment(name="myimg", build=ctx)
ml_client.environments.create_or_update(env)

with some work I find the job name of the relevant job that is running the docker build command, then I call

ml_client.jobs.stream(build_job_name)

This will correctly wait for the job to complete and print a status or error message when done. Meanwhile I don't see anything else, like the docker build log.

To Reproduce
Steps to reproduce the behavior:

1. invoke ml_client.jobs.stream(build_job_name) with a docker image build job in the prepare_image experiment
2. should print the full docker build log

Expected behavior
See above.

Additional context

After debugging I found two main bugs: 1. a mismatch of uri_folder to UriFolder values used as enums and 2. incorrectly parsing the credentials to access the std_log.txt file.
Will send a patch.