Change primitive name (#49)

* clean up

* add ml-stars to dep

Author: sarahmish

pyproject.toml

@@ -22,6 +22,7 @@ dependencies = [
     'pandas>=1.0.0,<2',
     'scikit-learn>=0.22.1,<2',
     'orion-ml>=0.6,<0.8',
+    'ml-stars>=0.2.1,<0.4',
     'openai>=1.46.0',
     'tiktoken>=0.7.0',
     'transformers>=4.44.2',

sigllm/core.py

@@ -16,7 +16,7 @@
 
 INTERVAL_PRIMITIVE = 'mlstars.custom.timeseries_preprocessing.time_segments_aggregate#1'
 DECIMAL_PRIMITIVE = 'sigllm.primitives.transformation.Float2Scalar#1'
-WINDOW_SIZE_PRIMITIVE = 'sigllm.primitives.forecasting.custom.rolling_window_sequences#1'
+WINDOW_SIZE_PRIMITIVE = 'mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1'
 
 
 class SigLLM(Orion):

sigllm/pipelines/detector/gpt_detector.json

@@ -3,7 +3,7 @@
         "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
         "sklearn.impute.SimpleImputer",
         "sigllm.primitives.transformation.Float2Scalar",
-        "sigllm.primitives.forecasting.custom.rolling_window_sequences",
+        "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
         "sigllm.primitives.transformation.format_as_string",
         "sigllm.primitives.forecasting.gpt.GPT",
         "sigllm.primitives.transformation.format_as_integer",
@@ -23,7 +23,7 @@
             "decimal": 2,
             "rescale": true
         },
-        "sigllm.primitives.forecasting.custom.rolling_window_sequences#1": {
+        "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
             "target_column": 0,
             "window_size": 140,
             "target_size": 1

sigllm/pipelines/detector/mistral_detector.json

@@ -3,7 +3,7 @@
         "mlstars.custom.timeseries_preprocessing.time_segments_aggregate",
         "sklearn.impute.SimpleImputer",
         "sigllm.primitives.transformation.Float2Scalar",
-        "sigllm.primitives.forecasting.custom.rolling_window_sequences",
+        "mlstars.custom.timeseries_preprocessing.rolling_window_sequences",
         "sigllm.primitives.transformation.format_as_string",
         "sigllm.primitives.forecasting.huggingface.HF",
         "sigllm.primitives.transformation.format_as_integer",
@@ -23,7 +23,7 @@
             "decimal": 2,
             "rescale": true
         },
-        "sigllm.primitives.forecasting.custom.rolling_window_sequences#1": {
+        "mlstars.custom.timeseries_preprocessing.rolling_window_sequences#1": {
             "target_column": 0,
             "window_size": 140,
             "target_size": 1

sigllm/primitives/forecasting/custom.py

@@ -190,7 +190,7 @@
        "['mlstars.custom.timeseries_preprocessing.time_segments_aggregate',\n",
        " 'sklearn.impute.SimpleImputer',\n",
        " 'sigllm.primitives.transformation.Float2Scalar',\n",
-       " 'sigllm.primitives.forecasting.custom.rolling_window_sequences',\n",
+       " 'mlstars.custom.timeseries_preprocessing.rolling_window_sequences',\n",
        " 'sigllm.primitives.transformation.format_as_string',\n",
        " 'sigllm.primitives.forecasting.huggingface.HF',\n",
        " 'sigllm.primitives.transformation.format_as_integer',\n",