Load a single ML Training Pipeline by id, fully typed for mutation-free
reads. Returns null when not found.
pipeline primary-key value
request user
the provider the read runs on (no global fallback)
Compute the next monotonic model version under a pipeline — max(Version)+1,
or 1 when the pipeline has no prior models. Implemented as a narrow,
read-only count/scan over MJ: ML Models.
pipeline primary-key value
request user
the provider the read runs on (no global fallback)
OptionalresolveResolve the sidecar driver key for an algorithm from its
MJ: ML Algorithms.DriverClass (e.g. xgboost, logistic_regression).
The pipeline view exposes Algorithm as the algorithm's display Name
(XGBoost, Multilayer Perceptron), which is NOT what the sidecar registry
keys on — it requires the lowercase DriverClass. The engine therefore
resolves the driver key by id rather than trusting the display name.
Optional so in-memory test fakes (which set pipeline.Algorithm directly to
the driver key) need not implement it — the engine falls back to
pipeline.Algorithm when this is absent or returns null.
MJ: ML Algorithms primary-key value
request user
the provider the read runs on (no global fallback)
the DriverClass driver key, or null when not found
Read seam for loading existing records (the training pipeline definition and the next-version lookup). Wraps
RunViewin production; tests inject canned rows. Never throws for logical read failures (mirrorsRunView).