Commit Graph

3 Commits

Author SHA1 Message Date
e4fc12e529 QTZPOC-20
QTZPOC-20: Enhance system robustness and test coverage across bundle processing, activity error handling, and worker operations.

*   Strengthen bundle reader validation with new tests for archive integrity, security vulnerabilities (e.g., path traversal, duplicate entries, special file types), and I/O error resilience.
*   Improve error handling and status propagation in PI Web API, MLflow, and OPC activities, including partial write scenarios and OPC session management.
*   Add comprehensive tests for worker startup, configuration, graceful shutdown, and Prometheus metrics server initialization.
*   Introduce a new utility for intelligent DataFrame debugging, summarizing large dataframes for concise logging, and refine exception chain summarization.
*   Update code coverage configuration to exclude @overload decorator lines.
2026-09-08 09:42:23 -03:00
dac4f1718f QTZPOC-20
QTZPOC-20: Implement model import workflow for .sientia bundles

Introduces the import_model workflow and its associated activities to enable importing .sientia bundles into MLflow and MongoDB. This includes:

*   New core workflow and activity logic for handling bundle download, decryption, validation, MLflow provisioning (experiments, runs, registered versions), and MongoDB model document creation.
*   Comprehensive E2E and unit test suites, including a dedicated test harness and a manual run script for development.
*   Updated .env.example and README.md with new configurations and usage instructions.
*   Ensures correct MLflow model source resolution for legacy loader compatibility and robust MongoDB document management.
*   Refactors existing utility scripts into a scripts/ directory.
2026-08-25 17:07:42 -03:00
0e445de386 QTZPOC-20
QTZPOC-20: Implement .sientia model bundle import workflow

Introduces a new Temporal workflow and activities to import .sientia model bundles. This enables:
- Secure decryption and validation of bundles through a seven-gate process.
- Provisioning imported models in MLflow and updating the MongoDB model listing.
- Comprehensive status tracking in the public.experiment_run table with new IMPORT_SUCCESS/IMPORT_ERROR states.
- Dedicated metrics, robust error handling, and configurable settings.
- Includes updated e2e database fixtures and extensive unit/integration tests for bundle format, reader, and overall workflow.
2026-08-25 10:40:46 -03:00