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Flexible MLflow workflow for lab/external users #1348

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@cpaniaguam

I'll bring it up in the dev meeting today, just leaving a note:

I think MLflow integration at the HSSM level can make sense, but we probably have to reflect on the actual use-case a little there.

  1. Linking HSSM runs to the network origin lineage, makes sense for initial proofing of bringing a network into production.
  2. One can imagine someone downstream (independent researcher) wanting to track their own numerical experiments, or even their literal overall data analysis workflows. In that case, the linkage to our oscar level file lineage might not be too useful.

I am concerning with making things useful for the latter case.

Originally posted by @AlexanderFengler in #1320 (comment)

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  1. linear-code commented on Sep 24, 2026

    @linear-code
  2. cpaniaguam commented on Sep 25, 2026

    @cpaniaguam
    CollaboratorAuthor

    @AlexanderFengler I think the framework introduced in #1320 is flexible enough to support both use cases with some adjustments in defaults and documentation.

    The scope I have in mind: make tracking flexible enough that someone working only in HSSM can record what they did and find it again.

    • A place for the user's own variables. Fits are recorded in detail already, but there is nowhere natural to put the dimensions they are actually varying — dataset version, priors, subset of subjects. Small addition, and the one thing clearly missing.
    • Documentation written for that user: recording your own fits, working locally with no server, ecosystem lineage as a later section rather than the opening premise.

    Anything more ambitious, such as recording model comparisons, computing comparison metrics automatically, we would rather leave until the basics have seen some use.

    Comments welcome, particularly if this is narrower than you had in mind.

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