Initial publishing commit

lib/python-beta/src/bailo/core/utils.py

@@ -11,3 +11,29 @@ def filter_none(json: dict[str, Any]) -> dict[str, Any]:
     """
     res = {k: v for k, v in json.items() if v is not None}
     return res
+
+
+class NestedDict(dict):
+    def __getitem__(self,keytuple):
+        # if key is not a tuple then access as normal
+        if not isinstance(keytuple, tuple):
+            return super(NestedDict,self).__getitem__(keytuple)
+        d = self
+        for key in keytuple:
+            d = d[key]
+        return d
+    def __setitem__(self, keytuple, item):
+        # if key is not a tuple then access as normal
+        if not isinstance(keytuple, tuple):
+            return super(NestedDict,self).__setitem__(keytuple, item)
+        d = self
+        for index, key in enumerate(keytuple):
+            if index != len(keytuple) - 1:
+                try:
+                    d = d[key]
+                except:
+                    d[key] = {}
+                    d = d[key]
+
+            else:
+                d[key] = item

lib/python-beta/src/bailo/helper/model.py

@@ -6,6 +6,7 @@
 from bailo.core.enums import ModelVisibility
 from bailo.helper.release import Release
 from bailo.core.exceptions import BailoException
+from bailo.core.utils import NestedDict
 
 from semantic_version import Version
 
@@ -316,12 +317,12 @@ def log_params(self, params: dict[str, Any]):
     def log_metrics(self, metrics: dict[str, Any]):
         self.run_data["metrics"].append(metrics)
 
-    def log_artifacts(self, artifacts: str):
+    def log_artifacts(self, artifacts: dict[str, Any]):
         self.run_data["artifiacts"].append(artifacts)
 
     def from_mlflow(self, tracking_uri: str, experiment_id: str):
         if ml_flow == 1:
-            client = mlflow.tracking.MlflowClient(tracking_uri=tracking_uri) #should this be here? or passed in?
+            client = mlflow.tracking.MlflowClient(tracking_uri=tracking_uri)
             runs = client.search_runs(experiment_id)
 
             for run in runs:
@@ -333,5 +334,17 @@ def from_mlflow(self, tracking_uri: str, experiment_id: str):
             raise ImportError("Optional MLFlow dependencies (needed for this method) are not installed.")
 
 
-    def publish(release_version: str, card_version: str):
-        pass
+    def publish(self, mc_loc: str, run_id: str):
+        mc = self.model.model_card
+        mc = NestedDict(mc)
+
+        for run in self.raw:
+            if run["run"] == run_id:
+                sel_run = run
+            else:
+                continue
+
+        sel_run = sel_run['params'] + sel_run['metrics'] 
+
+        mc[tuple(mc_loc.split('.'))] = sel_run
+        self.model.update_model_card(model_card=mc)