hopefully nlp fix

app.py

@@ -19,7 +19,7 @@ def sent_to_words(sentences):
     for sentence in sentences:
         yield(gensim.utils.simple_preprocess(str(sentence), deacc=True))  # deacc=True removes punctuations
         
-def lemmatization(texts, allowed_postags=['NOUN', 'ADJ', 'VERB', 'ADV']): #'NOUN', 'ADJ', 'VERB', 'ADV'
+def lemmatization(texts, allowed_postags=['NOUN', 'ADJ', 'VERB', 'ADV'], nlp=None): #'NOUN', 'ADJ', 'VERB', 'ADV'
     texts_out = []
     for sent in texts:
         doc = nlp(" ".join(sent))
@@ -46,9 +46,9 @@ def main(choose_context):
     print('downloading en_core_web_sm')
     os.system("python -m spacy download en_core_web_sm")
     print('en_core_web_sm downloaded')
-    
+
     nlp = spacy.load("en_core_web_sm", disable=["parser", "ner"])
-    data_lemmatized = lemmatization(data_words, allowed_postags=["NOUN", "ADJ"]) #select noun and verb
+    data_lemmatized = lemmatization(data_words, allowed_postags=["NOUN", "ADJ"], nlp=nlp) #select noun and verb
 
     vectorizer = CountVectorizer(
     analyzer='word',