some small changes

app.py

@@ -15,8 +15,10 @@ if 'response_content' not in st.session_state:
 # Creating main columns for the chat and runtime notifications
 chat_col = st.container()
 
-chat_col.title("CodeLATS")
-description = """This demo is an implementation of Language Agent Tree Search (LATS) (https://arxiv.org/abs/2310.04406) with Samba-1 in the backend. Thank you to the original authors of demo on which this is based from [Lapis Labs](https://lapis.rocks/)
+chat_col.title("SambaLATS")
+description = """This demo is an implementation of Language Agent Tree Search (LATS) (https://arxiv.org/abs/2310.04406) with Samba-1 in the backend. Thank you to the original authors of demo on which this is based from [Lapis Labs](https://lapis.rocks/)!
+
+Given Samba-1's lightning quick inference, not only can we accelerate our system's speeds but also improve our system's accuracy. Using many inference calls in this LATS style, we can solve programming questions with higher accuracy. In fact, this system reaches GPT-3.5 accuracy on HumanEval Python, 74% accuracy, with LLaMa 3 8B, taking 8 seconds on average. This is a 15.5% boost on LLaMa 3 8B alone. 
 
 Listed below is an example programming problem (https://leetcode.com/problems/median-of-two-sorted-arrays/description/) to get started with.