SIENTIAPDE-1273

Update version and enhance metrics calculation in Laborious system

- Updated image tag in values.yaml from 1.1.0 to 1.1.1.
- Modified GITHUB_BRANCH environment variable for consistency.
- Added a new method `calculate_simple_metrics` in model_metrics.py to compute various model performance metrics including RMSE, MSE, MAE, and R2.
- Integrated the new metrics calculation into the worker setup, allowing for concurrent processing of simple metrics.
- Updated tests to cover the new metrics calculation functionality, ensuring comprehensive validation of the implementation.

laborious/worker/worker.py

@@ -51,6 +51,8 @@ with workflow.unsafe.imports_passed_through():
     from laborious.workflows.minimal_retrain import MinimalRetrain
     from laborious.workflows.predictions_batch import PredictionsBatch
     from laborious.workflows.drift import Drift
+    from laborious.workflows.simple_metrics import SientiaMetrics
+    
     from laborious.workflows.sub_workflows.format_and_export_prediction import (
         FormatAndExportPrediction,
     )
@@ -175,6 +177,22 @@ async def main():
             workflow_task_poller_behavior=PollerBehaviorAutoscaling(),
             activity_task_poller_behavior=PollerBehaviorAutoscaling(),
         ),
+        Worker(
+            temporal_client,
+            task_queue='simple_metrics-queue',
+            workflows=[SimpleMetrics],
+            activities=[
+                activities.load_custom_query,
+                activities.calculate_simple_metrics,
+                activities.export_data_to_postgres,
+            ],
+            max_concurrent_workflow_tasks=50,
+            max_concurrent_activities=50,
+            max_concurrent_local_activities=50,
+            max_cached_workflows=2,
+            workflow_task_poller_behavior=PollerBehaviorAutoscaling(),
+            activity_task_poller_behavior=PollerBehaviorAutoscaling(),
+        ),
         Worker(
             temporal_client,
             task_queue='predictions_batch-queue',