Update app.py

app.py

@@ -9,10 +9,10 @@ import torch
 # Open the water_cycle.txt file in read mode with UTF-8 encoding
 with open("scholar_bot_knowledge.txt", "r", encoding="utf-8") as file:
   # Read the entire contents of the file and store it in a variable
-  water_cycle_text = file.read()
+  scholar_bot_text = file.read()
 
 # Print the text below
-print(water_cycle_text)
+print(scholar_bot_text)
 
 
 # STEP 3 FROM SEMANTIC SEARCH
@@ -43,7 +43,7 @@ def preprocess_text(text):
   return cleaned_chunks
 
 # Call the preprocess_text function and store the result in a cleaned_chunks variable
-cleaned_chunks = preprocess_text(water_cycle_text) # Complete this line
+cleaned_chunks = preprocess_text(scholar_bot_text) # Complete this line
 
 #STEP 4 FROM SEMANTIC SEARCH
 # Load the pre-trained embedding model that converts text to vectors