Update dependencies and enhance ML model retraining functionality
- Updated sientia-dataops-library version in requirements.txt from 1.3.3 to 1.3.4.
- Incremented image tag in values.yaml from 0.2.4 to 0.2.5 and added a new environment variable MONGODB_TTL_INDEX_HOURS.
- Introduced new methods in MLFlowRepository for model retraining and production model updates, including error handling and logging.
- Added retrain_model and update_production_model activities in mlflow.py to support model management workflows.
- Modified MongoDB connection settings in connectors_config.py for improved security and configuration flexibility.
Update GITHUB_BRANCH in values.yaml to reflect new stress testing branch and modify OPC error handling to set success flag instead of continuing on error.
Refactor OPC connection handling to improve error notifications and update GITHUB_BRANCH in values.yaml for MongoDB integration. Change requirements.txt to point to local dataops library path.
Update notification handler references to use CoreNotificationHandler and add MongoDB configuration to connectors. Update GITHUB_BRANCH in values.yaml for optimization tasks.
Update values.yaml to increase replicaCount to 5, change GITHUB_BRANCH to SIENTIAPDE-1141-criar-testes-de-carga, and adjust POSTGRES_MAX_CONNECTIONS to 30 for improved performance and testing.
SIENTIAPDE-1110 Refactor OPC activity to use server IDs instead of names, update values.yaml for OPC_ID, and enhance OpcRepository initialization for improved clarity and consistency.
