added commets

chatbot.py

@@ -18,10 +18,12 @@ def load_models():
     tokenizer = T5Tokenizer.from_pretrained('t5-small')
     generator = T5ForConditionalGeneration.from_pretrained('t5-base').to(device)
     return retriever, generator, tokenizer
+    print("Done loading models") 
 
 retriever, generator, tokenizer = load_models()
 
 def process_query(query):    
+    print("Processing...") 
     # Encode the query into a vector for semantic search using SentenceTransformer
     xq = retriever.encode([query]).tolist()
     # Query the Pinecone index for the most similar vector to the query