Completes OPEN-3569 Unify ModelSchema and ShellModelSchema for the Python API

Author: gustavocidornelas

examples/tabular-classification/sklearn/churn-classifier/churn-classifier-sklearn.ipynb

@@ -495,7 +495,10 @@
     "        \"model_type\": \"Logistic Regression\",\n",
     "        \"regularization\": \"None\",\n",
     "        \"encoder_used\": \"One Hot\",       \n",
-    "    }\n",
+    "    },\n",
+    "    \"classNames\": class_names,\n",
+    "    \"featureNames\": feature_names,\n",
+    "    \"categoricalFeatureNames\": categorical_feature_names,\n",
     "}\n",
     "\n",
     "with open(\"model_config.yaml\", \"w\") as model_config_file:\n",
@@ -835,7 +838,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.8.13"
   }
  },
  "nbformat": 4,

examples/tabular-classification/sklearn/fetal-health/fetal-health-sklearn.ipynb

@@ -423,7 +423,9 @@
     "    \"metadata\": {  # Can add anything here, as long as it is a dict\n",
     "        \"model_type\": \"Logistic Regression\",\n",
     "        \"regularization\": \"L1\",\n",
-    "    }\n",
+    "    },\n",
+    "    \"classNames\": class_names,\n",
+    "    \"featureNames\": feature_names,\n",
     "}\n",
     "\n",
     "with open(\"model_config.yaml\", \"w\") as model_config_file:\n",

examples/tabular-classification/sklearn/fraud-detection/fraud-classifier-sklearn.ipynb

@@ -524,7 +524,10 @@
     "        \"model_type\": \"Gradient Boosting\",\n",
     "        \"regularization\": \"None\",\n",
     "        \"encoder_used\": \"One Hot\",       \n",
-    "    }\n",
+    "    },\n",
+    "    \"classNames\": class_names,\n",
+    "    \"featureNames\": feature_names,\n",
+    "    \"categoricalFeatureNames\": categorical_feature_names,\n",
     "}\n",
     "\n",
     "with open(\"model_config.yaml\", \"w\") as model_config_file:\n",

examples/tabular-classification/sklearn/iris-classifier/iris-tabular-sklearn.ipynb

@@ -375,7 +375,9 @@
     "    \"metadata\": {  # Can add anything here, as long as it is a dict\n",
     "        \"model_type\": \"Logistic Regression\",\n",
     "        \"regularization\": \"None\",\n",
-    "    }\n",
+    "    },\n",
+    "    \"classNames\": class_names,\n",
+    "    \"featureNames\": feature_names,\n",
     "}\n",
     "\n",
     "with open(\"model_config.yaml\", \"w\") as model_config_file:\n",

openlayer/__init__.py

@@ -11,7 +11,7 @@
 
 from . import api, exceptions, utils, validators
 from .projects import Project
-from .schemas import BaselineModelSchema, DatasetSchema, ModelSchema, ShellModelSchema
+from .schemas import BaselineModelSchema, DatasetSchema, ModelSchema
 from .tasks import TaskType
 from .version import __version__  # noqa: F401
 
@@ -230,24 +230,7 @@ def add_model(
 
             .. admonition:: What's on the model config file?
 
-                The content of the YAML file depends on whether you are adding a shell
-                model or a model package.
-
-                **If you are adding a shell model**, the model configuration file
-                must contain the following fields:
-
-                - ``name`` : str
-                    Name of the model.
-                - ``architectureType`` : str
-                    The model's framework. Must be one of the supported frameworks
-                    on :obj:`ModelType`.
-                - ``metadata`` : Dict[str, any], default {}
-                    Dictionary containing metadata about the model. This is the
-                    metadata that will be displayed on the Openlayer platform.
-
-                **Alternatively, if you are adding a model package** (i.e., with model
-                artifacts and prediction interface), the model configuration file must
-                contain the following fields:
+                The model configuration YAML file must contain the following fields:
 
                 - ``name`` : str
                     Name of the model.
@@ -421,10 +404,7 @@ def add_model(
 
         # Load model config and augment with defaults
         model_config = utils.read_yaml(model_config_file_path)
-        if model_package_dir:
-            model_data = ModelSchema().load(model_config)
-        else:
-            model_data = ShellModelSchema().load(model_config)
+        model_data = ModelSchema().load(model_config)
 
         # Copy relevant resources to temp directory
         with tempfile.TemporaryDirectory() as temp_dir:

openlayer/schemas.py

@@ -104,6 +104,7 @@ class ModelSchema(ma.Schema):
     )
     classNames = ma.fields.List(
         ma.fields.Str(),
+        required=True,
     )
     name = ma.fields.Str(
         required=True,
@@ -156,28 +157,3 @@ class ProjectSchema(ma.Schema):
             + " https://reference.openlayer.com/reference/api/openlayer.TaskType.html.\n ",
         ),
     )
-
-
-class ShellModelSchema(ma.Schema):
-    """Schema for models without artifacts (i.e., shell model)."""
-
-    name = ma.fields.Str(
-        required=True,
-        validate=ma.validate.Length(
-            min=1,
-            max=64,
-        ),
-    )
-    metadata = ma.fields.Dict(
-        allow_none=True,
-        load_default={},
-    )
-    architectureType = ma.fields.Str(
-        validate=ma.validate.OneOf(
-            [model_framework.value for model_framework in ModelType],
-            error="`architectureType` must be one of the supported frameworks. "
-            + "Check out our API reference for a full list"
-            + " https://reference.openlayer.com/reference/api/openlayer.ModelType.html.\n ",
-        ),
-        required=True,
-    )

openlayer/validators.py

@@ -1021,10 +1021,7 @@ def _validate_model_config(self):
             with open(self.model_config_file_path, "r", encoding="UTF-8") as stream:
                 model_config = yaml.safe_load(stream)
 
-            if self.model_package_dir:
-                model_schema = schemas.ModelSchema()
-            else:
-                model_schema = schemas.ShellModelSchema()
+            model_schema = schemas.ModelSchema()
             try:
                 model_schema.load(model_config)
             except ma.ValidationError as err: