Update app.py

app.py

@@ -12,6 +12,7 @@ from torch.utils.data import DataLoader
 from PIL import Image
 
 device = torch.device('cpu')
+dev_mode = True
 
 
 #Spacy Initialization Section
@@ -117,10 +118,12 @@ def get_bert_embedding(review_text):
 def get_spaBert_embedding(entity):
     entity_index = entity_index_dict.get(entity.lower(), None)
     if entity_index is None:
-        #st.write("Got Bert embedding for: ", entity)
+        if(dev_mode == True):
+            st.write("Got Bert embedding for: ", entity)
         return get_bert_embedding(entity)                            #Fallback in-case SpaBERT could not resolve entity to retrieve embedding. Rare-cases only.
     else:
-        #st.write("Got SpaBert embedding for: ", entity)
+        if(dev_mode == True):
+            st.write("Got SpaBert embedding for: ", entity)
         return spaBERT_embeddings[entity_index]
 
         
@@ -135,7 +138,8 @@ def processSpatialEntities(review, nlp):
         if label in ['FAC', 'ORG', 'LOC', 'GPE']:  # Filter to geo-entities
             spaBert_emb = get_spaBert_embedding(text)
             token_embeddings.append(spaBert_emb)
-            st.write("Geo-Entity Found in review: ", text)
+            if(dev_mode == True)
+                st.write("Geo-Entity Found in review: ", text)
 
     token_embeddings = torch.stack(token_embeddings, dim=0)
     processed_embedding = token_embeddings.mean(dim=0)  # Shape: (768)
@@ -246,14 +250,14 @@ selected_review = example_reviews[user_input]
 if st.button("Highlight Geo-Entities"):
     if selected_review.strip():
         bert_embedding = get_bert_embedding(selected_review)
-        st.write("Review Embedding Shape:", bert_embedding.shape)
-        
         spaBert_embedding = processSpatialEntities(selected_review,nlp)
-        st.write("Geo-Entities embedding shape: ", spaBert_embedding.shape)
-
         combined_embedding = torch.cat((bert_embedding,spaBert_embedding),dim=-1)
-        st.write("Concatenated Embedding Shape:", combined_embedding.shape)
-        st.write("Concatenated Embedding:", combined_embedding)
+        
+        if(dev_mode == True):
+            st.write("Review Embedding Shape:", bert_embedding.shape)
+            st.write("Geo-Entities embedding shape: ", spaBert_embedding.shape)
+            st.write("Concatenated Embedding Shape:", combined_embedding.shape)
+            st.write("Concatenated Embedding:", combined_embedding)
 
         prediction = get_prediction(combined_embedding)