SIENTIAPDE-1251: Implement ML model training activity and repository
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.
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@@ -10,9 +10,10 @@ with workflow.unsafe.imports_passed_through():
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from model_manager.activities.gates import Gates
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from model_manager.activities.minio import MinIO
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from model_manager.activities.mlflow import MLFlow
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from model_manager.activities.training import Training
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class Activities(ExperimentTracking, MLFlow, MinIO, Gates):
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class Activities(ExperimentTracking, MLFlow, MinIO, Gates, Training):
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"""
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Main activities orchestrator for the Model Manager system.
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@@ -25,6 +26,7 @@ class Activities(ExperimentTracking, MLFlow, MinIO, Gates):
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- MLFlow: Model inference and transformation operations
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- MinIO: Object storage operations (file upload/download/delete)
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- Gates: Data quality validation and filtering mechanisms
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- Training: ML model training operations (extends BaseActivity)
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Attributes:
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postgres_config (dict): PostgreSQL connection configuration
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@@ -102,6 +104,8 @@ class Activities(ExperimentTracking, MLFlow, MinIO, Gates):
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Gates.__init__(self, logger=logger, notification_handler=notification_handler)
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Training.__init__(self, logger=logger, notification_handler=notification_handler)
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async def shutdown(self):
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"""
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Gracefully shutdown all activities and clean up resources.
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