SIENTIAPDE-1273

Refactor data handling in various modules to ensure DataFrame consistency

- Replaced direct DataFrame instantiation with `ensure_dataframe` utility in Gates, MLFlow, OPC, and ModelMetrics classes to standardize data handling.
- Updated return types in several asynchronous methods to return DataFrames instead of dictionaries for improved usability.
- Adjusted data export processes in workflows to convert DataFrames to dictionaries with `to_dict(orient='records')` for compatibility with downstream systems.

laborious/activities/model_metrics.py

@@ -138,7 +138,7 @@ class ModelMetrics(SientiaMonitoring):
 
 
     @activity.defn(name='calculate_drift')
-    async def calculate_drift(self, input_data: dict[str, Any]) -> dict[Hashable, Any]:
+    async def calculate_drift(self, input_data: dict[str, Any]) -> DataFrame | dict:
         """
         Calculate drift metrics for a model.
 
@@ -262,9 +262,9 @@ class ModelMetrics(SientiaMonitoring):
         self.debug(f'Drift dataframe: Size {drift_df.shape} \n{drift_df.head(5).to_string()}', metadata)
 
         
-        return drift_df.to_dict()
+        return drift_df
 
-    async def calculate_simple_metrics(self, input_data: dict[str, Any]) -> dict[Hashable, Any]:
+    async def calculate_simple_metrics(self, input_data: dict[str, Any]) -> DataFrame:
         """
         Calculate simple metrics for a model. Metrics available are:
             - rmse
@@ -342,6 +342,6 @@ class ModelMetrics(SientiaMonitoring):
 
         self.debug(f'Simple metrics dataframe: Size {data.shape} \n{data.head(5).to_string()}', metadata)
 
-        return data.to_dict()
+        return data