Hi guys, 
Which is the way through Databricks Asset Bundle to declare a new job definition having a serveless compute associated on each task that composes the workflow and be able that inside each notebook task definition is possible to catch the dependent custom libraries that I imported inside the workspace?

I did something like this:

      environments:
      - environment_key: envir
        spec:
          client: "1"
          dependencies:
            - "${workspace.root_path}/artifacts/.internal/data_pipelines-0.0.1-py3-none-any.whl"

      tasks:

        - task_key: schedule_next_run_for_this_job
          description: due to business requirements is needed to reschedule the workflow in the near next run
          environment_key: envir
          notebook_task:
            notebook_path: ../notebook/jobs/export.py
            base_parameters:
              function: schedule_next_run_for_this_job
              env: ${bundle.target}
              job_id: "{{job.id}}"
              workspace_url: "{{workspace.url}}"

but it returns to me:

Error: cannot create job: A task environment can not be provided for notebook task get_email_infos. Please use the %pip magic command to install notebook-scoped Python libraries and Python wheel packages

the only way to import personal wheel package inside a serveless compute is to install inside the notebook that library?

Because I want to do something like using:

libraries:
   - whl: ...