Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,4 +1,3 @@
-
 #!/usr/bin/env python3
 """
 LLM Compatibility Advisor - Streamlined with Download Sizes
@@ -224,26 +223,6 @@ def recommend_llm(ram_str) -> Tuple[str, str, str, Dict[str, List[Dict]]]:
                 "Research grade, maximum performance, domain expertise",
                 models)
 
-# Enhanced OS detection with better icons
-def get_os_info(os_name) -> Tuple[str, str]:
-    """Returns (icon, clean_name)"""
-    if pd.isna(os_name):
-        return "💻", "Not specified"
-    
-    os = str(os_name).lower()
-    if "windows" in os:
-        return "🪟", os_name
-    elif "mac" in os or "darwin" in os:
-        return "🍎", os_name
-    elif "linux" in os or "ubuntu" in os:
-        return "🐧", os_name
-    elif "android" in os:
-        return "🤖", os_name
-    elif "ios" in os:
-        return "📱", os_name
-    else:
-        return "💻", os_name
-
 # Performance visualization
 def create_performance_chart(df):
     """Create a performance distribution chart"""
@@ -361,12 +340,10 @@ if selected_user:
     
     with col1:
         st.markdown("### 💻 Laptop Configuration")
-        laptop_os_icon, laptop_os_name = get_os_info(user_data.get('Laptop Operating System'))
         laptop_ram = user_data.get('Laptop RAM', 'Not specified')
         laptop_rec, laptop_tier, laptop_info, laptop_models = recommend_llm(laptop_ram)
         laptop_ram_gb = extract_numeric_ram(laptop_ram) or 0
         
-        st.markdown(f"**OS:** {laptop_os_icon} {laptop_os_name}")
         st.markdown(f"**RAM:** {laptop_ram}")
         st.markdown(f"**Performance Tier:** {laptop_tier}")
         
@@ -380,12 +357,10 @@ if selected_user:
     
     with col2:
         st.markdown("### 📱 Mobile Configuration")
-        mobile_os_icon, mobile_os_name = get_os_info(user_data.get('Mobile Operating System'))
         mobile_ram = user_data.get('Mobile RAM', 'Not specified')
         mobile_rec, mobile_tier, mobile_info, mobile_models = recommend_llm(mobile_ram)
         mobile_ram_gb = extract_numeric_ram(mobile_ram) or 0
         
-        st.markdown(f"**OS:** {mobile_os_icon} {mobile_os_name}")
         st.markdown(f"**RAM:** {mobile_ram}")
         st.markdown(f"**Performance Tier:** {mobile_tier}")
         
@@ -415,7 +390,7 @@ df_display["Mobile LLM"] = mobile_recommendations
 df_display["Laptop Tier"] = laptop_tiers
 df_display["Mobile Tier"] = mobile_tiers
 
-# Filter based on sidebar selections (RAM range filter removed)
+# Filter based on sidebar selections
 mask = (laptop_tiers.isin(performance_filter) | mobile_tiers.isin(performance_filter))
 
 df_filtered = df_display[mask]