Update app.py

app.py

@@ -138,8 +138,8 @@ def processSpatialEntities(review, nlp):
             st.write("Geo-Entity Found in review: ", text)
 
     token_embeddings = torch.stack(token_embeddings, dim=0)
-    processed_embedding = token_embeddings.mean(dim=0, keepdim=True)
-    st.write("processed embedding shape: ", processed_embedding.shape)
+    processed_embedding = token_embeddings.mean(dim=0)  # Shape: (768)
+    processed_embedding = processed_embedding.unsqueeze(0)  # Shape: (1, 768)
     return processed_embedding
 
 
@@ -186,13 +186,10 @@ selected_review = example_reviews[user_input]
 if st.button("Highlight Geo-Entities"):
     if selected_review.strip():
         bert_embedding = get_bert_embedding(selected_review)
-        # Debug: Print the shape of the embeddings
-        st.write("Embedding Shape:", bert_embedding.shape)
+        st.write("Review Embedding Shape:", bert_embedding.shape)
         
-        # Debug: Print the embeddings themselves (optional)
-        #st.write("Embeddings:", bert_embedding)
-
         spaBert_embedding = processSpatialEntities(selected_review,nlp)
+        st.write("Geo-Entities embedding shape: ", spaBert_embedding.shape)
 
         #combine the embeddings (NOTE: come back and update after testing)
         combined_embedding = torch.cat((bert_embedding,spaBERT_embeddings[0]),dim=-1)