updated description

app.py

@@ -36,7 +36,8 @@ def get_response_from_gemini(prompt: str, key) -> str:
     return response.text.strip()
 
 def get_response_from_deepseek(prompt: str, key) -> str:
-    response = requests.post(
+    response = requests.
+post(
         url="https://openrouter.ai/api/v1/chat/completions",
         headers={"Authorization": f"Bearer {key}"},
         data=json.dumps({
@@ -181,8 +182,8 @@ st.markdown(
     unsafe_allow_html=True
 )
 
-st.title("Predicting Human Preference : Gemini vs DeepSeek")
-st.write("As part of this demo, we make use of two SOTA LLMs : [Gemini 2.5 Pro](https://deepmind.google/technologies/gemini/pro/) and [DeepSeek R1](https://api-docs.deepseek.com/news/news250120) and make them compete against each other on a given prompt (to be entered through the sidebar)")
+st.title("Predicting Human Preference : LLM Battleground")
+st.write("As part of this demo, we make use of any two of the following SOTA LLMs : [Gemini 2.5 Pro](https://deepmind.google/technologies/gemini/pro/), [DeepSeek R1](https://api-docs.deepseek.com/news/news250120), [Mistral Small 3.1](https://mistral.ai/news/mistral-small-3-1) and [LLaMa 4 Scout](https://ai.meta.com/blog/llama-4-multimodal-intelligence/) and make them compete against each other on a given prompt (to be entered through the sidebar)")
 st.write("Using our proposed hybrid model, we predict which response is more suited to be preferred by a human user.")
 
 st.sidebar.title("Ask a Question!")
@@ -221,7 +222,7 @@ if st.sidebar.button("Generate Responses") and question:
         })
 
 if st.session_state["generated"]:
-    tab1, tab2, tab3 = st.tabs(["Predictions","Model Architecture", "📈 Metric Curves"])
+    tab1, tab2, tab3 = st.tabs(["Predictions","Model Architecture", "Metric Curves"])
 
     with tab1:
         st.subheader("Model Responses")