Enhance README with code quality and validation guidelines
- Added a new section on code quality and validation tools, detailing the use of Ruff, mypy, Bandit, and pytest.
- Included installation instructions for development dependencies and options for running validation scripts.
- Provided best practices for maintaining code quality and integrating CI/CD workflows.
Enhance README and repository utilities for clarity and functionality
- Updated README.md to improve descriptions and structure, adding detailed sections for features, workflows, and architecture.
- Enhanced MinioRepository with comprehensive docstrings for methods and class attributes, improving usability and documentation.
- Refined MLFlowRepository with clearer method descriptions and improved logging for better observability and maintainability.
Update README.md to reflect new features and configuration changes
- Added details about two dedicated task queues: `predictions_batch-queue` and `minimal_retrain-queue`.
- Enhanced descriptions of activities and workflows, including multiple inheritance patterns and configurable MLFlow model serving.
- Updated monitoring metrics section to include new labels and metrics for prediction and OPC export operations.
- Revised configuration section with updated default values and added new environment variables for Kubernetes pod identification.
- Improved clarity in the Predictions Batch Workflow configuration example, including structured input filters and updated retention policies.
Update README.md to enhance installation instructions and refactor MLFlow filters
- Added steps for installing GitHub CLI and authenticating with GitHub.
- Updated the `api_error_filter` and `nan_values_filter` functions to improve parameter handling and streamline logic.
Update README.md to enhance architecture documentation
- Removed detailed system overview diagram to streamline content.
- Added architecture diagrams for key workflows: PredictionsBatch, PredictionProcess, FormatAndExportPrediction, and MinimalRetrain.
- Improved clarity and structure of the architecture principles section.
Update README.md to reflect changes in prediction workflow configuration
- Revised input parameters for the prediction process, including updates to schedule name, model ID, and workflow name.
- Enhanced structure of input filters and MLflow filter policies for improved clarity and functionality.
- Introduced new fields for model retention and output configuration, while maintaining backward compatibility with existing parameters.
Update README.md to reflect new prediction workflow configuration
- Revised input parameters for the prediction process, including changes to schedule name, model ID, and workflow type.
- Introduced new fields for workflow execution frequency, maximum retry policy, and query for data retrieval.
- Updated input and MLflow filter structures to enhance clarity and functionality.
- Added support for datetime columns and updated retention time for models.
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.
