switch from spacy to stanza for compatibility

model.py

@@ -12,14 +12,19 @@ device='cpu'
 # Declare the (trained) model that will be used
 classifier = transformers.pipeline("zero-shot-classification", model="simple_trained_wsd_pipeline", device=device)
 
-import spacy
+# import spacy
 # Part Of Speech tagging (POS tagging)
-nlp = spacy.load("en_core_web_sm")
+# nlp = spacy.load("en_core_web_sm")
 
 # Importing as module.
 # import en_core_web_sm
 # nlp = en_core_web_sm.load()
 
+import stanza
+
+# Initialize the English pipeline
+nlp = stanza.Pipeline('en')
+
 print('successfully download model')
 
 
@@ -69,8 +74,9 @@ def model(passage, level):
     ex1 = nlp(n)
 
     for word in ex1:
-      sentence_question_tag = n.replace(word.text, f"[{word.text}]")
-      text_dict[f"{word.lemma_} = {sentence_question_tag}"] = word.pos_
+      sentence_question_tag = n.replace(word.text, f"[{word.text}]") # spacy and stanza use the same entity tag: "word.text"
+      # text_dict[f"{word.lemma_} = {sentence_question_tag}"] = word.pos_ # this is for spacy
+      text_dict[f"{word.lemma} = {sentence_question_tag}"] = word.upos # this is for stanza
 
   # Collect the tagging results (filter in just NOUN, PROPN, VERB, ADJ, or ADV only)
   collector = {}

new_requirements.txt

@@ -147,11 +147,12 @@ smart-open==7.0.4
 sniffio==1.3.1
 soupsieve==2.6
 # spacy==3.7.6
-spacy<3.6.0
-spacy-legacy==3.0.12
-spacy-loggers==1.0.5
+# spacy<3.6.0
+# spacy-legacy==3.0.12
+# spacy-loggers==1.0.5
 srsly==2.4.8
 stack-data==0.6.3
+stanza==1.9.2 # use this instead of spacy
 sympy==1.13.2
 terminado==0.18.1
 text-unidecode==1.3
@@ -185,4 +186,4 @@ widgetsnbextension==3.6.8
 wrapt==1.16.0
 xxhash==3.5.0
 yarl==1.9.6
-https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.5.0/en_core_web_sm-3.5.0-py3-none-any.whl
+# https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.5.0/en_core_web_sm-3.5.0-py3-none-any.whl