rename and future steps

src/commands/train.py

@@ -148,8 +148,8 @@ def status(
             updates["registered_model_version"] = version
         st.update_training_job(job_name, **updates)
         if version:
-            st.set_latest_prerelease_model_version(version)
-            CONSOLE.print(f"MLflow model version: [cyan]{version}[/cyan] ([cyan]prerelease-latest[/cyan])")
+            st.set_latest_experiment_model_version(version)
+            CONSOLE.print(f"MLflow model version: [cyan]{version}[/cyan] ([cyan]experiment-latest[/cyan])")
     if run_id and cfg.mlflow.mode is not MlflowMode.disabled:
         CONSOLE.print("Open MLflow: [cyan]qc-cli infra mlflow-url[/cyan]")
 

src/state.py

@@ -48,8 +48,8 @@ class CliStateStore:
         state["training_jobs"] = jobs
         self._write(state)
 
-    def set_latest_prerelease_model_version(self, version: str) -> None:
-        self.update(latest_prerelease_model_version=version)
+    def set_latest_experiment_model_version(self, version: str) -> None:
+        self.update(latest_experiment_model_version=version)
 
     def _write(self, state: dict[str, Any]) -> None:
         with open(self.path, "w") as f:

src/tracking/mlflow.py

@@ -78,7 +78,9 @@ class MlflowTracker:
         self._log_params({f"hyperparameters.{key}": value for key, value in training_job.hyperparameters.items()})
         mlflow.set_tags(
             {
-                "qc_cli.stage": "prerelease",
+                "qc_cli.stage": "experiment",
+                "qc_cli.artifact_kind": "trained_source",
+                "qc_cli.source": "sagemaker",
                 "qc_cli.command": "train start",
                 "sagemaker.job_name": training_job.job_name,
             }
@@ -117,12 +119,14 @@ class MlflowTracker:
                 source=training_job_status.model_artifacts,
                 run_id=run_id,
                 tags={
-                    "qc_cli.stage": "prerelease",
+                    "qc_cli.stage": "experiment",
+                    "qc_cli.artifact_kind": "trained_source",
+                    "qc_cli.source": "sagemaker",
                     "sagemaker.job_name": training_job_status.name,
                 },
             )
             version_number = str(version.version)
-            client.set_registered_model_alias(self.registered_model_name, "prerelease-latest", version_number)
+            client.set_registered_model_alias(self.registered_model_name, "experiment-latest", version_number)
             mlflow.set_tag("qc_cli.registered_model_name", self.registered_model_name)
             mlflow.set_tag("qc_cli.registered_model_version", version_number)
             return version_number