Minor Updates

src/generation/generate_response.py

@@ -1,4 +1,5 @@
 # import libraries
+import time
 from src.retrieval.retriever_chain import get_base_retriever, load_hf_llm, create_qa_chain
 
 # constants
@@ -45,7 +46,11 @@ def generate_response(message, history):
     """
 
     # invoke chain
+    print("Question:", message)
+    start_time = time.time()
     response = global_qa_chain.invoke(message)
-    print(response)
+    print("Answer:", response)
+    end_time = time.time()
+    print("Response Time:", "{:.2f}".format(round(end_time - start_time, 2)))
 
     return response

src/indexing/build_indexes.py

@@ -35,9 +35,8 @@ def load_embedding_model():
         model_name=EMBEDDING_MODEL,
         model_kwargs={"device": device},
         encode_kwargs={
-            "normalize_embeddings": True
-        },  # set True to compute cosine similarity
-        cache_folder="./.cache"
+            "normalize_embeddings": True # set True to compute cosine similarity
+        }
     )
 
     # To get the value of the max sequence_length, we will query the underlying `SentenceTransformer` object used in the RecursiveCharacterTextSplitter.