Update app.py

app.py

@@ -9,24 +9,6 @@ from openprompt.prompts import ManualTemplate
 from openprompt.data_utils import InputExample
 from openprompt import PromptForClassification
 
-# def sentiment_analysis(sentence, template, positive, neutral, nagetive ):
-#     model_name = "bert-base-uncased" 
-#     nlp = pipeline("fill-mask", model=model_name)
-#     text = template.replace("[SENTENCE]",sentence)
-#     # return str(nlp(text))
-#     return sentence + template + positive + neutral + nagetive
-
-# demo = gr.Interface(fn=sentiment_analysis,
-#                     inputs = [gr.Textbox(placeholder="Enter sentence here.",label="sentence"),
-#                             gr.Textbox(placeholder="Your template must have a [SENTENCE] token and a [MASK] token.",label="template"),
-#                             gr.Textbox(placeholder="Separate words with Spaces.",label="positive"),
-#                             gr.Textbox(placeholder="Separate words with Spaces.",label="neutral"),
-#                             gr.Textbox(placeholder="Separate words with Spaces.",label="negative")
-#                             ],
-#                     outputs="text")
-    
-# demo.launch(server_port=8080)  
-
 def readLMwords():
     alldata = pd.read_csv("LoughranMcDonald_MasterDictionary_2020.csv")
     positive = list(alldata[alldata["Positive"]!=0]["Word"].str.lower())