rename BaseModel to ExtrasBaseModel

dff/script/extras/conditions/conditions.py

@@ -18,7 +18,7 @@
 
 from .dataset import DatasetItem
 from .utils import LABEL_KEY
-from .models.base_model import BaseModel
+from .models.base_model import ExtrasBaseModel
 
 
 @singledispatch
@@ -79,7 +79,7 @@ def has_cls_label_innner(ctx: Context, pipeline: Pipeline) -> bool:
 
 
 def has_match(
-    model: BaseModel,
+    model: ExtrasBaseModel,
     positive_examples: Optional[List[str]],
     negative_examples: Optional[List[str]] = None,
     threshold: float = 0.9,

dff/script/extras/conditions/models/base_model.py

@@ -1,7 +1,7 @@
 """
 Base Model
 -----------
-This module defines an abstract interface for label-scoring models, :py:class:`~BaseModel`.
+This module defines an abstract interface for label-scoring models, :py:class:`~ExtrasBaseModel`.
 When defining custom label-scoring models, always inherit from this class.
 """
 from copy import copy
@@ -13,7 +13,7 @@
 from ..utils import LABEL_KEY
 
 
-class BaseModel(ABC):
+class ExtrasBaseModel(ABC):
     """
     Base class for label-scoring models.
     Namespace key should be declared, if you want the scores of your model

dff/script/extras/conditions/models/huggingface.py

@@ -16,11 +16,11 @@
 except ImportError:
     hf_available = False
 
-from .base_model import BaseModel
+from .base_model import ExtrasBaseModel
 from ..dataset import Dataset
 
 
-class BaseHFModel(BaseModel):
+class BaseHFModel(ExtrasBaseModel):
     """
     Base class for Hugging Face-based annotator models.
 

dff/script/extras/conditions/models/local/classifiers/regex.py

@@ -8,7 +8,7 @@
 import re
 from typing import Optional, Union
 
-from ...base_model import BaseModel
+from ...base_model import ExtrasBaseModel
 from ....dataset import Dataset
 
 
@@ -34,7 +34,7 @@ def __call__(self, request: str, **re_kwargs):
         return result
 
 
-class RegexClassifier(BaseModel):
+class RegexClassifier(ExtrasBaseModel):
     """
     RegexClassifier wraps a :py:class:`~RegexModel` for label annotation.
 

dff/script/extras/conditions/models/local/cosine_matchers/gensim.py

@@ -18,13 +18,13 @@
     gensim_available = False
     ALL_MODELS = []
 
-from ...base_model import BaseModel
+from ...base_model import ExtrasBaseModel
 from ....dataset import Dataset
 from ....utils import DefaultTokenizer
 from .cosine_matcher_mixin import CosineMatcherMixin
 
 
-class GensimMatcher(CosineMatcherMixin, BaseModel):
+class GensimMatcher(CosineMatcherMixin, ExtrasBaseModel):
     """
     GensimMatcher utilizes embeddings from Gensim models to measure
     proximity between utterances and pre-defined labels.
@@ -47,7 +47,7 @@ def __init__(
         if not gensim_available:
             raise ImportError("Required packages missing. Try `pip install dff[ext,gensim]`")
         CosineMatcherMixin.__init__(self, dataset=dataset)
-        BaseModel.__init__(self, namespace_key=namespace_key)
+        ExtrasBaseModel.__init__(self, namespace_key=namespace_key)
         self.model = model
         self.tokenizer = tokenizer or DefaultTokenizer()
         # self.fit(self.dataset, **kwargs)

dff/script/extras/conditions/models/remote_api/async_mixin.py

@@ -7,11 +7,11 @@
 """
 from dff.script import Context
 
-from ..base_model import BaseModel
+from ..base_model import ExtrasBaseModel
 from ...utils import LABEL_KEY
 
 
-class AsyncMixin(BaseModel):
+class AsyncMixin(ExtrasBaseModel):
     """
     This class overrides the :py:meth:`~__call__` method
     allowing for asynchronous calls to annotator models.

dff/script/extras/conditions/models/remote_api/google_dialogflow_model.py

@@ -10,7 +10,7 @@
 import json
 from pathlib import Path
 
-from ..base_model import BaseModel
+from ..base_model import ExtrasBaseModel
 from .async_mixin import AsyncMixin
 
 try:
@@ -24,7 +24,7 @@
     dialogflow_available = False
 
 
-class AbstractGDFModel(BaseModel):
+class AbstractGDFModel(ExtrasBaseModel):
     """
     Abstract class for a Google Dialogflow model.
     """

dff/script/extras/conditions/models/remote_api/hf_api_model.py

@@ -21,11 +21,11 @@
 except ImportError:
     hf_api_available = False
 
-from ..base_model import BaseModel
+from ..base_model import ExtrasBaseModel
 from .async_mixin import AsyncMixin
 
 
-class AbstractHFAPIModel(BaseModel):
+class AbstractHFAPIModel(ExtrasBaseModel):
     """
     Abstract class for an HF API annotator.
     """

dff/script/extras/conditions/models/remote_api/rasa_model.py

@@ -22,11 +22,11 @@
 
 from http import HTTPStatus
 from ...utils import RasaResponse
-from ..base_model import BaseModel
+from ..base_model import ExtrasBaseModel
 from .async_mixin import AsyncMixin
 
 
-class AbstractRasaModel(BaseModel):
+class AbstractRasaModel(ExtrasBaseModel):
     """
     Abstract class for a RASA annotator.
     """

dff/script/extras/conditions/models/sklearn.py

@@ -23,10 +23,10 @@
     joblib = object
     sklearn_available = False
 
-from .base_model import BaseModel
+from .base_model import ExtrasBaseModel
 
 
-class BaseSklearnModel(BaseModel):
+class BaseSklearnModel(ExtrasBaseModel):
     """
     Base class for Sklearn-based annotator models.
 

docs/source/user_guides/extended_conditions.rst

@@ -102,10 +102,10 @@ The following code snippets demonstrate how you can write a connector for an ext
     from dff.script.extras.conditions.models.remote_api.async_mixin import (
         AsyncMixin,
     )
-    from dff.script.extras.conditions.models.base_model import BaseModel
+    from dff.script.extras.conditions.models.base_model import ExtrasBaseModel
 
 
-To create a synchronous connector to an API, we recommend you to inherit the class from ``BaseModel``.
+To create a synchronous connector to an API, we recommend you to inherit the class from ``ExtrasBaseModel``.
 The only method that you have to override is the ``predict`` method.
 It takes a request string and returns a {label: probability} dictionary.
 In case the request has not been successful, an empty dictionary can be returned.
@@ -118,7 +118,7 @@ We use `httpx` as an asynchronous http client.
 
 .. code-block:: python
 
-    class CustomAPIConnector(BaseModel):
+    class CustomAPIConnector(ExtrasBaseModel):
         def __init__(self, url: str, namespace_key: str = "default") -> None:
             super().__init__(namespace_key)
             self.url = url
@@ -156,12 +156,12 @@ In this section, we show the way you can adapt a classifier model to DFF's class
 
     import pickle
 
-    from dff.script.extras.conditions.models.base_model import BaseModel
+    from dff.script.extras.conditions.models.base_model import ExtrasBaseModel
 
 
-In order to create your own classifier, create a child class of the ``BaseModel`` abstract type.
+In order to create your own classifier, create a child class of the ``ExtrasBaseModel`` abstract type.
 
-``BaseModel`` only has one abstract method, ``predict``, that should necessarily be overridden.
+``ExtrasBaseModel`` only has one abstract method, ``predict``, that should necessarily be overridden.
 The method takes a request string and returns a dictionary of class labels
 and their respective probabilities.
 
@@ -174,7 +174,7 @@ at your own convenience, e.g. lack of those will not raise an error.
 
 .. code-block:: python
 
-    class MyCustomClassifier(BaseModel):
+    class MyCustomClassifier(ExtrasBaseModel):
         def __init__(
             self, swear_words: list, namespace_key: str = "default"
         ) -> None:
@@ -207,13 +207,13 @@ The following code snippets demonstrate the way in which a custom matcher can be
 
 .. code-block:: python
 
-    from dff.script.extras.conditions.models.base_model import BaseModel
+    from dff.script.extras.conditions.models.base_model import ExtrasBaseModel
     from dff.script.extras.conditions.models.local.cosine_matchers.cosine_matcher_mixin import (
         CosineMatcherMixin,
     )
 
 To build  your own cosine matcher, you should inherit
-from the ``CosineMatcherMixin`` and from the ``BaseModel``,
+from the ``CosineMatcherMixin`` and from the ``ExtrasBaseModel``,
 with the former taking precedence.
 This requires the ``__init__`` method to take ``dataset`` argument.
 
@@ -233,10 +233,10 @@ e.g. lack of those will not raise an error.
 
 .. code-block:: python
 
-    class MyCustomMatcher(CosineMatcherMixin, BaseModel):
+    class MyCustomMatcher(CosineMatcherMixin, ExtrasBaseModel):
         def __init__(self, model, dataset, namespace_key) -> None:
             CosineMatcherMixin.__init__(self, dataset)
-            BaseModel.__init__(self, namespace_key)
+            ExtrasBaseModel.__init__(self, namespace_key)
             self.model = model
 
         def transform(self, request: str):