SIENTIAPDE-1243: Rename project from 'laborious' to 'model-manager' across codebase and configuration. This includes updating project names in environment variables, Makefiles, README, metrics, and Helm chart values.

model_manager/worker/worker.py

@@ -1,7 +1,7 @@
 """
-Laborious Worker Module
+Model Manager Worker Module
 
-This module provides the main worker implementation for the Sientia DataOps Laborious system.
+This module provides the main worker implementation for the Sientia DataOps Model Manager system.
 It orchestrates Temporal workers, manages task queues, and handles the lifecycle of
 prediction and retraining workflows.
 
@@ -18,11 +18,11 @@ Key Features:
 
 Environment Variables:
 - TEMPORAL_HOST: Temporal server address (default: localhost:7233)
-- TEMPORAL_NAMESPACE: Temporal namespace (default: laborious)
+- TEMPORAL_NAMESPACE: Temporal namespace (default: model_manager)
 - POD_ID: Kubernetes pod identifier for metrics
 - HTTP_METRICS_PORT: Prometheus metrics server port (default: 9090)
 - HTTP_SDK_METRICS_PORT: Temporal SDK metrics port (default: 9091)
-- PROJECT_NAME: Project name for notifications (default: laborious)
+- PROJECT_NAME: Project name for notifications (default: model_manager)
 """
 
 from temporalio import workflow, client
@@ -56,7 +56,7 @@ SDK_METRICS_PORT = int(os.getenv('HTTP_SDK_METRICS_PORT', "9091"))
 
 async def main():
     """
-    Main entry point for the Laborious worker application.
+    Main entry point for the Model Manager worker application.
 
     This function initializes and starts all components of the worker:
     1. Sets up logging and metadata
@@ -97,7 +97,7 @@ async def main():
         connection_string=mongo_config['connection_string'],
         database=mongo_config['database_name'],
         logger=logger,
-        project_name=os.getenv('PROJECT_NAME', 'laborious')
+        project_name=os.getenv('PROJECT_NAME', 'model-manager')
     )
 
     logger.custom_info('Starting Activities...', metadata)
@@ -127,7 +127,7 @@ async def main():
 
     temporal_client = await client.Client.connect(
         target_host=host,
-        namespace=os.getenv('TEMPORAL_NAMESPACE', 'laborious'),
+        namespace=os.getenv('TEMPORAL_NAMESPACE', 'model-manager'),
         runtime=new_runtime
     )
 
@@ -214,7 +214,7 @@ def start_prometheus_server():
     and sets the application health metric to indicate the service is running.
 
     The server exposes metrics that can be scraped by Prometheus for monitoring
-    the health and performance of the Laborious worker.
+    the health and performance of the Model Manager worker.
 
     Environment Variables:
         HTTP_METRICS_PORT: Port for the metrics server (default: 9090)