commented out lftk function

app.py

@@ -16,26 +16,26 @@ llama_model = AutoModelForCausalLM.from_pretrained("daryl149/llama-2-7b-chat-hf"
 
 template_single = '''Please output any <{}> in the following sentence one per line without any additional text: "{}"'''
 
-def linguistic_features(message):
-    # Load a trained spaCy pipeline
-    nlp = spacy.load("en_core_web_sm")
+# def linguistic_features(message):
+#     # Load a trained spaCy pipeline
+#     nlp = spacy.load("en_core_web_sm")
 
-    # Create a spaCy doc object
-    doc = nlp(message)
+#     # Create a spaCy doc object
+#     doc = nlp(message)
 
-    # Initiate LFTK extractor by passing in the doc
-    LFTK_extractor = lftk.Extractor(docs=doc)
+#     # Initiate LFTK extractor by passing in the doc
+#     LFTK_extractor = lftk.Extractor(docs=doc)
 
-    # Customize LFTK extractor (optional)
-    LFTK_extractor.customize(stop_words=True, punctuations=False, round_decimal=3)
+#     # Customize LFTK extractor (optional)
+#     LFTK_extractor.customize(stop_words=True, punctuations=False, round_decimal=3)
 
-    # Use LFTK to dynamically extract handcrafted linguistic features
-    features_to_extract = lftk.search_features(family="wordsent", language="general", return_format="list_key")
-    extracted_features = LFTK_extractor.extract(features=features_to_extract)
+#     # Use LFTK to dynamically extract handcrafted linguistic features
+#     features_to_extract = lftk.search_features(family="wordsent", language="general", return_format="list_key")
+#     extracted_features = LFTK_extractor.extract(features=features_to_extract)
 
-    print('Linguistic Features:', extracted_features)
+#     print('Linguistic Features:', extracted_features)
 
-    return extracted_features
+#     return extracted_features
 
 
 def update_api_key(new_key):
@@ -295,7 +295,7 @@ def interface():
             task_btn.click(llama_strategies_respond, inputs=[strategy3, task, task_linguistic_entities, task_prompt, llama_S3_chatbot], 
                       outputs=[task, task_prompt, llama_S3_chatbot])
             
-            # Event Handler for GPT 3.5 Chatbot, user must submit api key before submitting the prompt
+            # Event Handler for GPT 3.5 Chatbot POS/Chunk, user must submit api key before submitting the prompt
             # Will activate after getting API key
             # task_apikey_btn.click(update_api_key, inputs=ling_ents_apikey_input)
             # task_btn.click(gpt_strategies_respond, inputs=[strategy1, task, task_linguistic_entities, gpt_S1_chatbot],