- Modified `.env.example` to set local defaults for PostgreSQL, MLflow, and MinIO configurations. - Added MongoDB configuration parameters to the environment setup. - Updated `README.md` to reflect changes in workflow input parameters and task queue naming conventions. - Removed the `ModelServing` class to streamline the codebase, as it was deemed unnecessary. - Adjusted `connectors_config.py` to align with new environment variable names and improve clarity. - Updated tests to reflect changes in configuration handling and removed tests related to the deleted `ModelServing` class.
1.9 KiB
1.9 KiB
Insert a new experiment run
-- Optional: remove a previous run with the same id
DELETE FROM public.experiment_run WHERE experiment_run_id = 1001;
INSERT INTO public.experiment_run
(experiment_name, run_name, username, status, error_message, created_at,
updated_at, bucket_name, file_name, request_data, orchestrator_response_data)
VALUES(
'test-experiment-name',
'test-run-name',
'test-username',
'ORCHESTRATOR_WAITING_PROC',
null,
now(),
now(),
'model-training',
'training_data.csv',
'{"experiment_run_id":1001,"variable_columns":["feature_a","feature_b"],"target_variable":"target","bucket_name":"model-training","file_name":"training_data.csv","line_separator":",","decimal_separator":".","train_size":80,"shuffle":true,"model_name":"Linear Regression","model_type":"linear_regression","data_model_kwargs":{},"model_kwargs":{},"opt_params":{},"model_metadata":{"schemas":{"components":{"schemas":{}}}}}',
null
);
Upload the input dataset to MinIO
mc cp input_dataset.csv suse/model-training/training-sample-dataset-1001.csv
Temporal input payload sample
Keys match TrainModelParams.from_dict in model_manager/utils/models/train_model_params.py: every field passed to _check_none must be present; model_metadata must be non-empty for validate_business_rules(). Omit optional keys (date_column, date_format, random_state, val_file_name, model_id) when defaults or None apply.
{
"experiment_run_id": 1001,
"variable_columns": ["feature_a", "feature_b"],
"target_variable": "target",
"bucket_name": "model-training",
"file_name": "training-sample-dataset-1001.csv",
"line_separator": ",",
"decimal_separator": ".",
"train_size": 80,
"shuffle": true,
"random_state": 42,
"model_name": "test-runtime-linear-regression-model",
"model_type": "linear_regression",
"model_id": 1001,
"data_model_kwargs": {},
"model_kwargs": {},
"opt_params": {}
}