Update app.py

app.py

@@ -153,7 +153,8 @@ nltk.download('averaged_perceptron_tagger')
 #     return outputs.last_hidden_state.mean(dim=1).squeeze().numpy()
 
 
-
+import numpy as np
+import sentencepiece as sp
 from transformers import pipeline
 # Load a summarization model
 summarizer = pipeline("summarization")
@@ -246,7 +247,6 @@ from sklearn.feature_extraction.text import TfidfVectorizer
 from sklearn.metrics import silhouette_score
 from bertopic import BERTopic
 from collections import Counter
-import numpy as np
 
 
 def extract_problem_domains(df,