update

app.py

@@ -42,7 +42,7 @@ def preprocess_text(text):
   # Return the cleaned_chunks
   return cleaned_chunks
 
-cleaned_chunks = preprocess_text(academic_tips_text)
+cleaned_chunks = preprocess_text(poverty_and_education)
 
 
 # Load the pre-trained embedding model that converts text to vectors
@@ -100,7 +100,6 @@ def get_top_chunks(query, chunk_embeddings, text_chunks):
   # Return the list of most relevant chunks
   return top_chunks
 
-cleaned_chunks = preprocess_text(poverty_and_education)
 # Print the top results
 print(top_results)