make "latest" the default alias for model (DAT-1052)

datamint/api/endpoints/deploy_model_api.py

@@ -7,6 +7,7 @@
 
 import httpx
 
+from datamint.configs import DEFAULT_DEPLOY_MODEL_ALIAS
 from datamint.entities.deployjob import DeployJob
 from datamint.exceptions import JobTimeoutError, ResourceNotFoundError
 
@@ -182,7 +183,7 @@ def remove_image(self, model_name: str, tag: str | None = None) -> dict:
         response = self._make_request('DELETE', f'/{self.endpoint_base}/image/{model_name}', params=params)
         return response.json()
 
-    def image_exists(self, model_name: str, tag: str = "latest") -> bool:
+    def image_exists(self, model_name: str, tag: str = DEFAULT_DEPLOY_MODEL_ALIAS) -> bool:
         """Check if a model image exists."""
         params = {'tag': tag}
         response = self._make_request('GET', f'/{self.endpoint_base}/image/{model_name}/exists', params=params)

datamint/api/endpoints/model_types.py

@@ -7,6 +7,7 @@
 from mlflow.entities.model_registry import RegisteredModel as MlflowRegisteredModel
 
 from datamint._repr_utils import render_html_card, render_text_block
+from datamint.configs import DEFAULT_DEPLOY_MODEL_ALIAS
 from datamint.entities.annotations.annotation_spec import AnnotationSpec
 from datamint.mlflow.flavors.datamint_flavor import FLAVOR_NAME
 from datamint.mlflow.models.tags import DATAMINT_LOGGED_MODEL_ID_TAG
@@ -198,7 +199,7 @@ def get_metrics(self, version: ModelVersion | None = None) -> dict[str, float]:
         version = version or self.get_latest_version()
         return version.get_metrics() if version else {}
 
-    def is_deployed(self, tag: str = 'latest') -> bool:
+    def is_deployed(self, tag: str = DEFAULT_DEPLOY_MODEL_ALIAS) -> bool:
         return self._api._deploy_api.image_exists(self.name, tag=tag)
 
     def get_projects(self) -> list['Project']:

datamint/client_cmd_tools/datamint_init.py

@@ -413,7 +413,7 @@
 api = Api()
 
 # Deploy the model registered during training. This can take a few minutes.
-deploy_job = api.deploy.start(model_name=MODEL_NAME, model_alias="latest")
+deploy_job = api.deploy.start(model_name=MODEL_NAME)
 print(f"Deploying '{MODEL_NAME}'... (this may take a few minutes)")
 
 deploy_job = deploy_job.wait()
@@ -428,7 +428,6 @@
 
 inf_job = api.inference.submit(
     model_name=MODEL_NAME,
-    model_alias="latest",
     resource_id=resource.id,
 )
 inf_job = inf_job.wait()
@@ -860,7 +859,7 @@
 api = Api()
 
 # Deploy the model registered during training. This can take a few minutes.
-deploy_job = api.deploy.start(model_name=MODEL_NAME, model_alias="latest")
+deploy_job = api.deploy.start(model_name=MODEL_NAME)
 print(f"Deploying '{MODEL_NAME}'... (this may take a few minutes)")
 
 deploy_job = deploy_job.wait()
@@ -875,7 +874,6 @@
 
 inf_job = api.inference.submit(
     model_name=MODEL_NAME,
-    model_alias="latest",
     resource_id=resource.id,
 )
 inf_job = inf_job.wait()
@@ -1344,7 +1342,7 @@ def _overlay(ax, img_np, anns):
 api = Api()
 
 # Deploy the model registered during training. This can take a few minutes.
-deploy_job = api.deploy.start(model_name=MODEL_NAME, model_alias="latest")
+deploy_job = api.deploy.start(model_name=MODEL_NAME)
 print(f"Deploying '{MODEL_NAME}'... (this may take a few minutes)")
 
 deploy_job = deploy_job.wait()
@@ -1359,7 +1357,6 @@ def _overlay(ax, img_np, anns):
 
 inf_job = api.inference.submit(
     model_name=MODEL_NAME,
-    model_alias="latest",
     resource_id=resource.id,
 )
 inf_job = inf_job.wait()

datamint/configs.py

@@ -17,6 +17,8 @@
     APIURL_KEY: 'https://api.datamint.io'
 }
 
+DEFAULT_DEPLOY_MODEL_ALIAS = 'latest'
+
 _LOGGER = logging.getLogger(__name__)
 
 DIRS = PlatformDirs(appname='datamintapi')

datamint/exceptions.py

@@ -1,3 +1,6 @@
+from datamint.configs import DEFAULT_DEPLOY_MODEL_ALIAS
+
+
 class DatamintException(Exception):
     """Base class for all Datamint exceptions."""
 
@@ -139,7 +142,7 @@ def __str__(self) -> str:
             ref = f"{self.model_name}:{self.model_alias}"
             deploy_kwarg = f"model_alias='{self.model_alias}'"
         else:
-            ref = f"{self.model_name}:champion"
+            ref = f"{self.model_name}:{DEFAULT_DEPLOY_MODEL_ALIAS}"
             deploy_kwarg = None
 
         deploy_call = f"api.deploy_model.start('{self.model_name}'"