feat(model): _convert_model doesnt need classname anymore

Author: ehdsouza

ibm_watson/assistant_v1.py

@@ -132,15 +132,15 @@ def message(self,
         if workspace_id is None:
             raise ValueError('workspace_id must be provided')
         if input is not None:
-            input = self._convert_model(input, MessageInput)
+            input = self._convert_model(input)
         if intents is not None:
-            intents = [self._convert_model(x, RuntimeIntent) for x in intents]
+            intents = [self._convert_model(x) for x in intents]
         if entities is not None:
-            entities = [self._convert_model(x, RuntimeEntity) for x in entities]
+            entities = [self._convert_model(x) for x in entities]
         if context is not None:
-            context = self._convert_model(context, Context)
+            context = self._convert_model(context)
         if output is not None:
-            output = self._convert_model(output, OutputData)
+            output = self._convert_model(output)
 
         headers = {}
         if 'headers' in kwargs:
@@ -277,20 +277,15 @@ def create_workspace(self,
         """
 
         if system_settings is not None:
-            system_settings = self._convert_model(system_settings,
-                                                  WorkspaceSystemSettings)
+            system_settings = self._convert_model(system_settings)
         if intents is not None:
-            intents = [self._convert_model(x, CreateIntent) for x in intents]
+            intents = [self._convert_model(x) for x in intents]
         if entities is not None:
-            entities = [self._convert_model(x, CreateEntity) for x in entities]
+            entities = [self._convert_model(x) for x in entities]
         if dialog_nodes is not None:
-            dialog_nodes = [
-                self._convert_model(x, DialogNode) for x in dialog_nodes
-            ]
+            dialog_nodes = [self._convert_model(x) for x in dialog_nodes]
         if counterexamples is not None:
-            counterexamples = [
-                self._convert_model(x, Counterexample) for x in counterexamples
-            ]
+            counterexamples = [self._convert_model(x) for x in counterexamples]
 
         headers = {}
         if 'headers' in kwargs:
@@ -442,20 +437,15 @@ def update_workspace(self,
         if workspace_id is None:
             raise ValueError('workspace_id must be provided')
         if system_settings is not None:
-            system_settings = self._convert_model(system_settings,
-                                                  WorkspaceSystemSettings)
+            system_settings = self._convert_model(system_settings)
         if intents is not None:
-            intents = [self._convert_model(x, CreateIntent) for x in intents]
+            intents = [self._convert_model(x) for x in intents]
         if entities is not None:
-            entities = [self._convert_model(x, CreateEntity) for x in entities]
+            entities = [self._convert_model(x) for x in entities]
         if dialog_nodes is not None:
-            dialog_nodes = [
-                self._convert_model(x, DialogNode) for x in dialog_nodes
-            ]
+            dialog_nodes = [self._convert_model(x) for x in dialog_nodes]
         if counterexamples is not None:
-            counterexamples = [
-                self._convert_model(x, Counterexample) for x in counterexamples
-            ]
+            counterexamples = [self._convert_model(x) for x in counterexamples]
 
         headers = {}
         if 'headers' in kwargs:
@@ -629,7 +619,7 @@ def create_intent(self,
         if intent is None:
             raise ValueError('intent must be provided')
         if examples is not None:
-            examples = [self._convert_model(x, Example) for x in examples]
+            examples = [self._convert_model(x) for x in examples]
 
         headers = {}
         if 'headers' in kwargs:
@@ -752,9 +742,7 @@ def update_intent(self,
         if intent is None:
             raise ValueError('intent must be provided')
         if new_examples is not None:
-            new_examples = [
-                self._convert_model(x, Example) for x in new_examples
-            ]
+            new_examples = [self._convert_model(x) for x in new_examples]
 
         headers = {}
         if 'headers' in kwargs:
@@ -924,7 +912,7 @@ def create_example(self,
         if text is None:
             raise ValueError('text must be provided')
         if mentions is not None:
-            mentions = [self._convert_model(x, Mention) for x in mentions]
+            mentions = [self._convert_model(x) for x in mentions]
 
         headers = {}
         if 'headers' in kwargs:
@@ -1036,9 +1024,7 @@ def update_example(self,
         if text is None:
             raise ValueError('text must be provided')
         if new_mentions is not None:
-            new_mentions = [
-                self._convert_model(x, Mention) for x in new_mentions
-            ]
+            new_mentions = [self._convert_model(x) for x in new_mentions]
 
         headers = {}
         if 'headers' in kwargs:
@@ -1476,7 +1462,7 @@ def create_entity(self,
         if entity is None:
             raise ValueError('entity must be provided')
         if values is not None:
-            values = [self._convert_model(x, CreateValue) for x in values]
+            values = [self._convert_model(x) for x in values]
 
         headers = {}
         if 'headers' in kwargs:
@@ -1606,9 +1592,7 @@ def update_entity(self,
         if entity is None:
             raise ValueError('entity must be provided')
         if new_values is not None:
-            new_values = [
-                self._convert_model(x, CreateValue) for x in new_values
-            ]
+            new_values = [self._convert_model(x) for x in new_values]
 
         headers = {}
         if 'headers' in kwargs:
@@ -2498,13 +2482,11 @@ def create_dialog_node(self,
         if dialog_node is None:
             raise ValueError('dialog_node must be provided')
         if output is not None:
-            output = self._convert_model(output, DialogNodeOutput)
+            output = self._convert_model(output)
         if next_step is not None:
-            next_step = self._convert_model(next_step, DialogNodeNextStep)
+            next_step = self._convert_model(next_step)
         if actions is not None:
-            actions = [
-                self._convert_model(x, DialogNodeAction) for x in actions
-            ]
+            actions = [self._convert_model(x) for x in actions]
 
         headers = {}
         if 'headers' in kwargs:
@@ -2678,14 +2660,11 @@ def update_dialog_node(self,
         if dialog_node is None:
             raise ValueError('dialog_node must be provided')
         if new_output is not None:
-            new_output = self._convert_model(new_output, DialogNodeOutput)
+            new_output = self._convert_model(new_output)
         if new_next_step is not None:
-            new_next_step = self._convert_model(new_next_step,
-                                                DialogNodeNextStep)
+            new_next_step = self._convert_model(new_next_step)
         if new_actions is not None:
-            new_actions = [
-                self._convert_model(x, DialogNodeAction) for x in new_actions
-            ]
+            new_actions = [self._convert_model(x) for x in new_actions]
 
         headers = {}
         if 'headers' in kwargs:

ibm_watson/assistant_v2.py

@@ -203,9 +203,9 @@ def message(self,
         if session_id is None:
             raise ValueError('session_id must be provided')
         if input is not None:
-            input = self._convert_model(input, MessageInput)
+            input = self._convert_model(input)
         if context is not None:
-            context = self._convert_model(context, MessageContext)
+            context = self._convert_model(context)
 
         headers = {}
         if 'headers' in kwargs:

ibm_watson/compare_comply_v1.py

@@ -338,7 +338,7 @@ def add_feedback(self,
 
         if feedback_data is None:
             raise ValueError('feedback_data must be provided')
-        feedback_data = self._convert_model(feedback_data, FeedbackDataInput)
+        feedback_data = self._convert_model(feedback_data)
 
         headers = {}
         if 'headers' in kwargs:

ibm_watson/discovery_v1.py

@@ -365,18 +365,13 @@ def create_configuration(self,
         if name is None:
             raise ValueError('name must be provided')
         if conversions is not None:
-            conversions = self._convert_model(conversions, Conversions)
+            conversions = self._convert_model(conversions)
         if enrichments is not None:
-            enrichments = [
-                self._convert_model(x, Enrichment) for x in enrichments
-            ]
+            enrichments = [self._convert_model(x) for x in enrichments]
         if normalizations is not None:
-            normalizations = [
-                self._convert_model(x, NormalizationOperation)
-                for x in normalizations
-            ]
+            normalizations = [self._convert_model(x) for x in normalizations]
         if source is not None:
-            source = self._convert_model(source, Source)
+            source = self._convert_model(source)
 
         headers = {}
         if 'headers' in kwargs:
@@ -527,18 +522,13 @@ def update_configuration(self,
         if name is None:
             raise ValueError('name must be provided')
         if conversions is not None:
-            conversions = self._convert_model(conversions, Conversions)
+            conversions = self._convert_model(conversions)
         if enrichments is not None:
-            enrichments = [
-                self._convert_model(x, Enrichment) for x in enrichments
-            ]
+            enrichments = [self._convert_model(x) for x in enrichments]
         if normalizations is not None:
-            normalizations = [
-                self._convert_model(x, NormalizationOperation)
-                for x in normalizations
-            ]
+            normalizations = [self._convert_model(x) for x in normalizations]
         if source is not None:
-            source = self._convert_model(source, Source)
+            source = self._convert_model(source)
 
         headers = {}
         if 'headers' in kwargs:
@@ -1039,7 +1029,7 @@ def create_expansions(self, environment_id, collection_id, expansions,
             raise ValueError('collection_id must be provided')
         if expansions is None:
             raise ValueError('expansions must be provided')
-        expansions = [self._convert_model(x, Expansion) for x in expansions]
+        expansions = [self._convert_model(x) for x in expansions]
 
         headers = {}
         if 'headers' in kwargs:
@@ -1169,8 +1159,7 @@ def create_tokenization_dictionary(self,
             raise ValueError('collection_id must be provided')
         if tokenization_rules is not None:
             tokenization_rules = [
-                self._convert_model(x, TokenDictRule)
-                for x in tokenization_rules
+                self._convert_model(x) for x in tokenization_rules
             ]
 
         headers = {}
@@ -2235,9 +2224,9 @@ def query_entities(self,
         if collection_id is None:
             raise ValueError('collection_id must be provided')
         if entity is not None:
-            entity = self._convert_model(entity, QueryEntitiesEntity)
+            entity = self._convert_model(entity)
         if context is not None:
-            context = self._convert_model(context, QueryEntitiesContext)
+            context = self._convert_model(context)
 
         headers = {}
         if 'headers' in kwargs:
@@ -2313,13 +2302,11 @@ def query_relations(self,
         if collection_id is None:
             raise ValueError('collection_id must be provided')
         if entities is not None:
-            entities = [
-                self._convert_model(x, QueryRelationsEntity) for x in entities
-            ]
+            entities = [self._convert_model(x) for x in entities]
         if context is not None:
-            context = self._convert_model(context, QueryEntitiesContext)
+            context = self._convert_model(context)
         if filter is not None:
-            filter = self._convert_model(filter, QueryRelationsFilter)
+            filter = self._convert_model(filter)
 
         headers = {}
         if 'headers' in kwargs:
@@ -2423,9 +2410,7 @@ def add_training_data(self,
         if collection_id is None:
             raise ValueError('collection_id must be provided')
         if examples is not None:
-            examples = [
-                self._convert_model(x, TrainingExample) for x in examples
-            ]
+            examples = [self._convert_model(x) for x in examples]
 
         headers = {}
         if 'headers' in kwargs:
@@ -2893,7 +2878,7 @@ def create_event(self, type, data, **kwargs):
             raise ValueError('type must be provided')
         if data is None:
             raise ValueError('data must be provided')
-        data = self._convert_model(data, EventData)
+        data = self._convert_model(data)
 
         headers = {}
         if 'headers' in kwargs:
@@ -3284,8 +3269,7 @@ def create_credentials(self,
         if environment_id is None:
             raise ValueError('environment_id must be provided')
         if credential_details is not None:
-            credential_details = self._convert_model(credential_details,
-                                                     CredentialDetails)
+            credential_details = self._convert_model(credential_details)
 
         headers = {}
         if 'headers' in kwargs:
@@ -3400,8 +3384,7 @@ def update_credentials(self,
         if credential_id is None:
             raise ValueError('credential_id must be provided')
         if credential_details is not None:
-            credential_details = self._convert_model(credential_details,
-                                                     CredentialDetails)
+            credential_details = self._convert_model(credential_details)
 
         headers = {}
         if 'headers' in kwargs:

ibm_watson/natural_language_classifier_v1.py

@@ -130,7 +130,7 @@ def classify_collection(self, classifier_id, collection, **kwargs):
             raise ValueError('classifier_id must be provided')
         if collection is None:
             raise ValueError('collection must be provided')
-        collection = [self._convert_model(x, ClassifyInput) for x in collection]
+        collection = [self._convert_model(x) for x in collection]
 
         headers = {}
         if 'headers' in kwargs:

ibm_watson/natural_language_understanding_v1.py

@@ -151,7 +151,7 @@ def analyze(self,
 
         if features is None:
             raise ValueError('features must be provided')
-        features = self._convert_model(features, Features)
+        features = self._convert_model(features)
 
         headers = {}
         if 'headers' in kwargs:

ibm_watson/personality_insights_v3.py

@@ -189,7 +189,7 @@ def profile(self,
         if accept is None:
             raise ValueError('accept must be provided')
         if isinstance(content, Content):
-            content = self._convert_model(content, Content)
+            content = self._convert_model(content)
 
         headers = {
             'Accept': accept,

ibm_watson/speech_to_text_v1.py

@@ -1782,7 +1782,7 @@ def add_words(self, customization_id, words, **kwargs):
             raise ValueError('customization_id must be provided')
         if words is None:
             raise ValueError('words must be provided')
-        words = [self._convert_model(x, CustomWord) for x in words]
+        words = [self._convert_model(x) for x in words]
 
         headers = {}
         if 'headers' in kwargs:

ibm_watson/text_to_speech_v1.py

@@ -489,7 +489,7 @@ def update_voice_model(self,
         if customization_id is None:
             raise ValueError('customization_id must be provided')
         if words is not None:
-            words = [self._convert_model(x, Word) for x in words]
+            words = [self._convert_model(x) for x in words]
 
         headers = {}
         if 'headers' in kwargs:
@@ -634,7 +634,7 @@ def add_words(self, customization_id, words, **kwargs):
             raise ValueError('customization_id must be provided')
         if words is None:
             raise ValueError('words must be provided')
-        words = [self._convert_model(x, Word) for x in words]
+        words = [self._convert_model(x) for x in words]
 
         headers = {}
         if 'headers' in kwargs: