- Added a new fixture to manage runtime report artifacts in a writable temp directory during E2E tests, addressing permission issues in local CI/dev environments.
- Updated `conftest.py` to include a requirements.txt file in the model packaging path for training activities.
- Refactored existing fixtures to use `pytest.fixture` instead of `pytest_asyncio.fixture` for better compatibility.
- Enhanced the `Reports` class to include a target alias for report metrics, ensuring compatibility with Evidently's reporting requirements.
- Introduced new test scenarios to validate the handling of missing and whitespace-only `date_column` inputs in the training workflow.
These changes improve the robustness of the E2E testing framework and enhance the clarity of model reporting metrics.
- Added a method to persist computed regression metrics (MSE, MAE, R²) as MLflow parameters during model training, enhancing model evaluation and tracking.
- Updated the Training class to log the equation path if available, improving artifact management.
- Introduced PROJECT_BASE_PATH constant for consistent project directory reference.
- Updated Reports class to require template_path for loading HTML templates.
- Modified DataManagerRepository to pass the new template_path when generating reports.
- Removed exception handling in load_html_from_file for cleaner code.
- Added debug print statements in the Reports class to log output directory, report path, and base path for better traceability during report generation.
- Added target_name parameter to Reports class for improved report context.
- Updated inject_content function to ensure proper handling of HTML sections.
- Modified DataManagerRepository to join predictions with training and validation data for accurate report generation.
