42a7e82c82
SIENTIAPDE-1241: Suppress sklearn FutureWarning regarding 'squared' deprecation.
2025-10-22 18:28:13 -03:00
5789a13023
SIENTIAPDE-1241: refactor train_model workflow due to I/O errors.
2025-10-22 15:37:56 -03:00
Bruno Domingues
f2a1c88ff3
Merge pull request #8 from Aignosi/feature/SIENTIAPDE-1255
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SIENTIAPDE-1255: Refactor Model Manager for Training Pipeline, Integrate Sientia MLOps Library, and Add Unit Tests
2025-10-21 09:42:17 -03:00
ab7c93480b
SIENTIAPDE-1255: Refactor: Move extra pip requirements to environment variable and use constants for preprocessor steps.
2025-10-21 09:20:23 -03:00
4686b438db
SIENTIAPDE-1255: Update quality gate workflow: Remove redundant repository and disk space cleanup, update cache key.
2025-10-20 22:35:20 -03:00
3e52253a98
SIENTIAPDE-1255: Add tests to ensure get_required_columns removes columns from self_operations and cross_operations.
2025-10-20 22:27:58 -03:00
614eb0cb7f
SIENTIAPDE-1255: Add unit tests for utils.split_train_test function
2025-10-20 22:22:38 -03:00
089f312575
SIENTIAPDE-1255: Add unit tests for the reports module
2025-10-20 22:20:26 -03:00
0de2ece063
SIENTIAPDE-1255: Add unit tests for sientia models (DataPreprocessor and LinearRegressionModel)
2025-10-20 20:59:55 -03:00
3c09e59f6a
SIENTIAPDE-1255: Add unit tests for the ModelServing class.
2025-10-20 20:24:50 -03:00
b1fe62f68b
SIENTIAPDE-1255: Add unit tests for sientia metrics module (MAE, MSE, R2)
2025-10-20 20:13:08 -03:00
b3e4bb8660
SIENTIAPDE-1255: Add comprehensive tests for __del__ methods in Activities and ExperimentTracking to ensure proper resource cleanup and exception handling.
2025-10-20 20:09:49 -03:00
4a32d712ba
SIENTIAPDE-1255: Implement object destructors for Activities and ExperimentTracking to prevent AttributeError during garbage collection, and mock workflow logger in tests to avoid RuntimeWarning.
2025-10-20 17:53:49 -03:00
52be5c4e8e
SIENTIAPDE-1255: Improve documentation for split_train_test function in utils.py
2025-10-20 17:41:05 -03:00
0dbe179367
SIENTIAPDE-1255: Add thread-safety documentation and I/O notes to Reports class, improve save_all_sections documentation and error handling.
2025-10-20 17:38:44 -03:00
2292ae57cc
SIENTIAPDE-1255: Add thread-safety documentation and in-place modification warnings to LinearRegressionModel and DataPreprocessor classes.
2025-10-20 17:27:58 -03:00
56f3db350c
SIENTIAPDE-1255: Refactor ModelServing class to improve thread safety, resource management, and documentation. Adds context manager for experiment saving and clarifies thread-safety concerns.
2025-10-20 17:16:45 -03:00
56a21a16da
SIENTIAPDE-1255: Integrate sientia-mlops-library into model-manager, adding model serving, reporting, and updated model definitions.
2025-10-20 16:55:52 -03:00
9e31ab679b
SIENTIAPDE-1255: Implement MLFlow artifact management and model persistence
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This commit introduces a new model_repository.py to handle MLFlow artifact generation and model persistence. It also updates the README to reflect this change and modifies training_repository.py to separate training and MLFlow operations.
2025-10-17 09:11:54 -03:00
a66b996cc1
SIENTIAPDE-1255: Refactor MLFlow activities for training operations and update metrics
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This commit refactors the MLFlow activities to focus on model training rather than prediction operations. It removes prediction-related activities and metrics, and updates the MLFlow activity descriptions to reflect the change in focus. The README is also updated to reflect these changes.
2025-10-17 00:51:29 -03:00
85a8ba1e68
SIENTIAPDE-1255: Refactor data quality gates to training focused metrics and repositories. This commit removes the data quality gates and filters, focusing on training-specific metrics and data repositories. It also updates the README to reflect these changes, including new training metrics and a streamlined data services section.
2025-10-17 00:39:06 -03:00
e191e7849f
SIENTIAPDE-1255: Refactor Model Manager to focus on ML model training pipeline and simplify architecture. This includes removing prediction workflows, updating core functionality, and improving parameter validation and resource management.
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README.md | 411 deletions(-) 117 insertions(+)
1 file changed, 117 insertions(+), 411 deletions(-)
2025-10-16 18:26:56 -03:00
7abd951806
SIENTIAPDE-1255: Refactor worker to support only the train_model-queue and remove prediction workflows.
2025-10-16 18:15:52 -03:00
8f1cc21bb1
SIENTIAPDE-1255: Add port forwarding setup script and documentation to README.md
2025-10-16 18:00:28 -03:00
Bruno Domingues
9ee12373b4
Merge pull request #7 from Aignosi/feature/SIENTIAPDE-1253
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SIENTIAPDE-1253: Improve Train Model Workflow with Enhanced Error Handling, Validation, and Cleanup
2025-10-15 17:04:49 -03:00
4ff796a56f
SIENTIAPDE-1253: Update README.md to include documentation for the Train Model workflow and renumber the Minimal Retrain workflow. (+101, -1)
2025-10-15 16:35:13 -03:00
98c216733b
SIENTIAPDE-1253: Enhance error logging in train_model workflow with rich context for debugging.
2025-10-15 16:19:15 -03:00
305a39b44c
SIENTIAPDE-1253: Implement business rule validation for training parameters. Adds a validate_business_rules method to the TrainModelParams class to enforce constraints on training parameters, improving data integrity and preventing errors. Also updates tests to include target variable in variable columns and adds tests for business rule validations.
2025-10-15 16:16:09 -03:00
4b28d5f1c8
SIENTIAPDE-1253: Implement granular retry policies for activities in train_model workflow.
2025-10-15 16:06:13 -03:00
780184769d
SIENTIAPDE-1253: Expose workflow activity timeouts as environment variables and document them.
2025-10-15 16:03:01 -03:00
1ec40bfb2a
SIENTIAPDE-1253: Implement activity for cleaning up temporary run directory and integrate into train model workflow. This change introduces a new activity for idempotent cleanup of the run directory after model training, replacing the direct directory removal in the workflow. This improves determinism and error handling. Also includes unit tests for the new activity.
2025-10-15 15:49:05 -03:00
8ea98360c3
SIENTIAPDE-1253: Refactor training workflow and activities to raise exceptions on failure
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This commit refactors the training workflow and associated activities to raise exceptions on failure instead of returning success/failure dictionaries. This allows the Temporal workflow to handle errors more effectively and ensures that the workflow stops when a critical error occurs.
Key changes:
- The train_model workflow is introduced to orchestrate the entire training process, including parameter validation, data download, model training, and model saving.
- The validate_train_params activity is added to validate and convert training parameters.
- The train_model and save_model activities are updated to raise exceptions on failure.
- The ExperimentStatus enum is updated to include a new status for orchestrator validation errors.
- The tests are updated to reflect the new exception-based error handling.
- The activities now return the TrainModelResult directly instead of a dictionary.
2025-10-15 15:19:29 -03:00
61267ec49d
SIENTIAPDE-1253: Enforce TrainModelParams object in Training activity and tests, removing dict conversion.
2025-10-14 10:03:34 -03:00
Bruno Domingues
014e1cd910
Merge pull request #6 from Aignosi/feature/SIENTIAPDE-1252
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SIENTIAPDE-1252: Implement Model Saving to MLflow and Artifact Logging
2025-10-13 14:44:39 -03:00
9d4ec19586
SIENTIAPDE-1252: Improve caching in quality gate, add alt text to logo, and change exception type in MLflow repository.
2025-10-13 10:54:38 -03:00
b3c749872c
SIENTIAPDE-1252: Implement save_model activity to save trained models to MLflow with comprehensive error handling and add corresponding unit tests.
2025-10-13 10:18:45 -03:00
3fd5ab79fe
SIENTIAPDE-1252: Implement artifact generation and MLflow logging for model training results
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This commit introduces artifact generation and MLflow logging capabilities to the model training process. It includes the following changes:
- Added methods to generate reports, save data files, and log model parameters, metrics, models, and artifacts to MLflow.
- Implemented error handling for various scenarios, such as missing files, invalid data, and MLflow connection errors.
- Created a new 'header.html' file for report styling and navigation.
- Modified the 'model_repository.py' file to include the new artifact generation and MLflow logging methods.
- Added comprehensive unit tests to ensure the functionality and robustness of the new features.
2025-10-10 17:56:09 -03:00
52b7b23261
SIENTIAPDE-1252: Update Python setup action and simplify dependency caching in quality gate workflow
2025-10-09 17:52:35 -03:00
94e11df803
SIENTIAPDE-1252: Remove experiment_description from TrainModelParams and related tests.
2025-10-09 17:48:43 -03:00
Bruno Domingues
5b0cd92dfe
Merge pull request #5 from Aignosi/feature/SIENTIAPDE-1251
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Implement ML Model Training Activity and Repository (SIENTIAPDE-1251)
2025-10-09 17:09:56 -03:00
bee6036205
SIENTIAPDE-1251: Implement ML model training activity and repository
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This commit introduces the 'Training' activity and 'TrainingRepository' for handling ML model training operations within the Model Manager system.
- Added model_manager/activities/training.py for the Training activity, which extends BaseActivity and integrates with Temporal workflows.
- Added model_manager/utils/repository/training_repository.py for the TrainingRepository, which encapsulates the core training logic.
- Updated model_manager/activities/activities.py to include the Training activity in the main activities orchestrator.
- Updated README.md to document the new 'Training' component.
- Added unit tests for the new activity and repository.
2025-10-09 15:07:27 -03:00
Bruno Domingues
c970754e1b
Merge pull request #4 from Aignosi/feature/SIENTIAPDE-1250
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SIENTIAPDE-1250: Implement Experiment Tracking Activity and Refactor Test Structure
2025-10-07 14:51:14 -03:00
97f5ee08f1
SIENTIAPDE-1250: Fix: Update pip cache key and replace pytz with datetime.UTC in experiment tracking.
2025-10-07 14:12:35 -03:00
7e1eace77f
SIENTIAPDE-1250: Implement experiment tracking activity with status updates, error handling, and model registration. This includes a unified update method, error message truncation, and integration into the main activities orchestrator. (236+, 2-)
2025-10-07 11:27:23 -03:00
2628dc92d2
SIENTIAPDE-1250: Refactor: Remove 'laborious' directory from test structure and update README.md accordingly.
2025-10-07 10:02:38 -03:00
Bruno Domingues
851f34c80e
Merge pull request #3 from Aignosi/feature/SIENTIAPDE-1249
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Implement data models for Model Manager
2025-10-06 19:53:28 -03:00
04c94efd98
SIENTIAPDE-1249: Refactor TrainModelParams to use dataclass and add from_dict method for validation, remove no-cache-dir from pip install in quality gate workflow, and rename X_train/X_test to x_train/x_test in TrainModelResult.
2025-10-06 19:11:02 -03:00
d8583cdae7
SIENTIAPDE-1249: Implement data models for Model Manager and add unit tests. This commit introduces data transfer objects (DTOs) and model classes for experiment status, training parameters, and training results, along with corresponding unit tests to ensure their correct behavior.
2025-10-06 16:49:18 -03:00
Bruno Domingues
18ccfed78a
Merge pull request #2 from Aignosi/feature/SIENTIAPDE-1248
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SIENTIAPDE-1248: Integrate MinIO, Add Worker Tests, and Refactor Documentation
2025-10-06 11:27:19 -03:00
520975e7aa
SIENTIAPDE-1248: Refactor MinIO activity to raise specific exception types for better error handling
2025-10-06 10:58:48 -03:00
