Register and stage models
DearDiary.Model and DearDiary.ModelVersion form a project-scoped registry on top of the run-tracking entities. A Model is the named bucket that downstream serving code refers to (e.g. "fraud-classifier"); a ModelVersion is a concrete checkpoint with lineage back to the Iteration that produced it, an optional pointer at the artifact bytes in any configured storage backend, and a lifecycle DearDiary.Stage.
Versions transition through NO_STAGE → STAGING → PRODUCTION → ARCHIVED. Promoting a version to PRODUCTION automatically demotes whichever sibling was previously in PRODUCTION, preserving the "at most one production version per model" invariant.
Scaffold a project and an iteration
julia> project_id, _ = create_project("Fraud detection");julia> experiment_id, _ = create_experiment(project_id, DearDiary.IN_PROGRESS, "DT sweep");julia> iteration_id, _ = create_iteration(experiment_id);julia> create_parameter(iteration_id, "max_depth", 7);julia> create_metric(iteration_id, "accuracy", 0.96);
Save the trained model bytes as a Resource. Any serialisation format works; the registry cares only about the byte payload and its lineage.
julia> checkpoint_bytes = rand(UInt8, 1024);julia> resource_id, _ = create_resource(experiment_id, "fraud-clf.jlso", checkpoint_bytes);
Register the model
A Model is a named entry: the human-readable handle that survives across hundreds of training runs.
julia> model_id, _ = create_model(project_id, "fraud-classifier");julia> get_model(model_id)DearDiary.Model ├ id = "639a08a8-b269-4e35-97b7-119089ebd505" ├ project_id = "b3228828-e9c5-4ecf-a597-990da82708bc" ├ name = "fraud-classifier" ├ description = "" ├ created_date = 2026-07-19T05:20:31.622 └ updated_date = nothing
Register a version
A ModelVersion ties a Resource to the Iteration that produced it. The per-model version number is assigned by the server (gap-free, monotonic, unique within the model):
julia> version_a_id, _ = create_modelversion(
model_id, iteration_id, resource_id,
"Decision tree, max_depth=7",
);julia> version_a = get_modelversion(version_a_id)DearDiary.ModelVersion ├ id = "54c61621-a095-4fac-9ac6-9dfbdbec971e" ├ model_id = "639a08a8-b269-4e35-97b7-119089ebd505" ├ version = 1 ├ iteration_id = "2cfce950-b539-4126-86ab-692f849a305d" ├ resource_id = "854c49b5-ca22-4509-9eb2-295097a79cc3" ├ stage_id = 1 ├ description = "Decision tree, max_depth=7" ├ created_date = 2026-07-19T05:20:31.844 └ updated_date = nothing
A freshly registered version starts in DearDiary.NO_STAGE. Promote it through the lifecycle as the model proves itself in evaluation:
julia> update_modelversion(version_a_id, DearDiary.STAGING, nothing, nothing);julia> update_modelversion(version_a_id, DearDiary.PRODUCTION, nothing, nothing);Roll forward to a new checkpoint
Train another iteration, register a second version, and promote it to PRODUCTION. The previous incumbent is auto-archived in the same transaction:
julia> iteration_b_id, _ = create_iteration(experiment_id);julia> create_parameter(iteration_b_id, "max_depth", 9);julia> create_metric(iteration_b_id, "accuracy", 0.974);julia> resource_b_id, _ = create_resource(experiment_id, "fraud-clf-v2.jlso", rand(UInt8, 1024));julia> version_b_id, _ = create_modelversion( model_id, iteration_b_id, resource_b_id, "Decision tree, max_depth=9", );julia> update_modelversion(version_b_id, DearDiary.PRODUCTION, nothing, nothing);
The previous production version is now archived:
julia> get_modelversion(version_a_id).stage_id == (DearDiary.ARCHIVED |> Integer)true
julia> get_modelversion(version_b_id).stage_id == (DearDiary.PRODUCTION |> Integer)true
Browsing the registry
get_modelversions returns the per-model history ordered by version ascending, so finding the current production checkpoint is a single filter:
julia> versions = get_modelversions(model_id);julia> production = filter(v -> v.stage_id == (DearDiary.PRODUCTION |> Integer), versions);julia> production[1].version2
The full lineage is reachable from version.iteration_id and version.resource_id:
julia> producing_iteration = (version_b_id |> get_modelversion).iteration_id |> get_iterationDearDiary.Iteration ├ id = "52c9af3b-6a0d-43dc-bc91-18b5d0699846" ├ experiment_id = "2f9f8551-4615-43ae-b1ee-beeeeafa0dce" ├ notes = "" ├ created_date = 2026-07-19T05:20:32.258 ├ end_date = nothing ├ parent_iteration_id = nothing ├ status_id = 1 ├ error_message = "" ├ julia_version = "" ├ git_sha = "" ├ git_dirty = false ├ entrypoint = "" ├ project_toml = "" └ manifest_toml = ""
julia> get_parameters(producing_iteration.id)1-element Vector{DearDiary.Parameter}: DearDiary.Parameter ├ id = "12a46bf9-6102-4f5a-b032-89e0f8bbdf9a" ├ iteration_id = "52c9af3b-6a0d-43dc-bc91-18b5d0699846" ├ key = "max_depth" └ value = "9"