SIENTIAPDE-1182

Remove Docker configuration files and refactor project structure

- Deleted docker-compose.yml and Dockerfile as part of the project restructuring.
- Updated README.md to reflect changes in project setup and configuration.
- Introduced a new __init__.py file in the laborious package to provide an overview of the system.
- Enhanced documentation across various modules, including metrics, activities, and workflows, to improve clarity and usability.
- Added comprehensive docstrings and comments to key classes and methods for better maintainability.

laborious/worker/worker.py

@@ -1,3 +1,30 @@
+"""
+Laborious Worker Module
+
+This module provides the main worker implementation for the Sientia DataOps Laborious system.
+It orchestrates Temporal workers, manages task queues, and handles the lifecycle of
+prediction and retraining workflows.
+
+The worker supports two main task queues:
+- predictions_batch-queue: Handles batch prediction workflows
+- minimal_retrain-queue: Handles model retraining workflows
+
+Key Features:
+- Automatic scaling with PollerBehaviorAutoscaling
+- Prometheus metrics integration
+- Comprehensive error handling and logging
+- Graceful shutdown with cleanup
+- Multiple worker instances for different workflow types
+
+Environment Variables:
+- TEMPORAL_HOST: Temporal server address (default: localhost:7233)
+- TEMPORAL_NAMESPACE: Temporal namespace (default: laborious)
+- 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)
+"""
+
 from temporalio import workflow, client
 from temporalio.worker import Worker, PollerBehaviorAutoscaling
 from temporalio.runtime import Runtime, TelemetryConfig, PrometheusConfig
@@ -28,6 +55,25 @@ SDK_METRICS_PORT = int(os.getenv('HTTP_SDK_METRICS_PORT', "9091"))
 
 
 async def main():
+    """
+    Main entry point for the Laborious worker application.
+
+    This function initializes and starts all components of the worker:
+    1. Sets up logging and metadata
+    2. Starts Prometheus metrics server
+    3. Initializes notification handler
+    4. Creates and configures activities
+    5. Initializes OPC connections
+    6. Starts Temporal client and workers
+    7. Manages worker lifecycle and graceful shutdown
+
+    The function runs indefinitely until interrupted or an error occurs.
+    On error, it performs cleanup and exits with a non-zero status code.
+
+    Raises:
+        Exception: Any unhandled exception during worker execution
+        SystemExit: On graceful shutdown or error conditions
+    """
     host = os.getenv('TEMPORAL_HOST', 'localhost:7233')
     logger = get_logger(__name__)
 
@@ -161,6 +207,22 @@ async def main():
 
 
 def start_prometheus_server():
+    """
+    Starts the Prometheus metrics server for monitoring and observability.
+
+    This function initializes the Prometheus HTTP server on the configured port
+    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.
+
+    Environment Variables:
+        HTTP_METRICS_PORT: Port for the metrics server (default: 9090)
+        POD_ID: Pod identifier for metrics labeling
+
+    Raises:
+        SystemExit: If the metrics server fails to start
+    """
     try:
         port = int(os.getenv("HTTP_METRICS_PORT", 9090))
         start_http_server(port)