Update src/streamlit_app.py

src/streamlit_app.py

@@ -596,43 +596,42 @@ if selected_ram_key in LLM_DATABASE and selected_category in LLM_DATABASE[select
     st.subheader(f"🎯 {selected_category.title()} Models for {selected_ram_range}")
     
     # Display models in a detailed table
-   # Inside the for loop displaying each model
-with st.container():
-    col1, col2, col3 = st.columns([3, 1, 3])
-    with col1:
-        st.markdown(f"### {model['name']}")
-    with col2:
-        st.markdown(f"**{model['size']}**")
-        st.caption("Download Size")
-    with col3:
-        st.markdown(f"*{model['description']}*")
-        # Add download suggestion
-        if "Llama" in model['name']:
-            st.caption("🔗 Hugging Face & Ollama")
-        elif "Mistral" in model['name']:
-            st.caption("🔗 Hugging Face & Mistral AI")
-        elif "Gemma" in model['name']:
-            st.caption("🔗 Hugging Face & Google")
-        else:
-            st.caption("🔗 Hugging Face")
-
-    # 🔽 Quantization size details
-    fp16, q8, q4 = calculate_quantized_sizes(model['size'])
-    with st.expander("💾 Quantized Size Estimates"):
-        st.markdown(f"""
-        | Format | Size |
-        |--------|------|
-        | FP16 (Full Precision) | **{fp16}** |
-        | 8-bit Quantized       | **{q8}** |
-        | 4-bit Quantized       | **{q4}** |
-        """)
-    
-    
+    for model in models:
+        with st.container():
+            col1, col2, col3 = st.columns([3, 1, 3])
+            with col1:
+                st.markdown(f"### {model['name']}")
+            with col2:
+                st.markdown(f"**{model['size']}**")
+                st.caption("Download Size")
+            with col3:
+                st.markdown(f"*{model['description']}*")
+                if "Llama" in model['name']:
+                    st.caption("🔗 Available on Hugging Face & Ollama")
+                elif "Mistral" in model['name']:
+                    st.caption("🔗 Available on Hugging Face & Mistral AI")
+                elif "Gemma" in model['name']:
+                    st.caption("🔗 Available on Hugging Face & Google")
+                else:
+                    st.caption("🔗 Available on Hugging Face")
+            
+            # 🔽 Quantization size details
+            fp16, q8, q4 = calculate_quantized_sizes(model['size'])
+            with st.expander("💾 Quantized Size Estimates"):
+                st.markdown(f"""
+                | Format | Size |
+                |--------|------|
+                | FP16 (Full Precision) | **{fp16}** |
+                | 8-bit Quantized       | **{q8}** |
+                | 4-bit Quantized       | **{q4}** |
+                """)
+    
+    st.markdown("---")  # ✅ this belongs inside the if block
 
-st.markdown("---")
 else:
     st.info(f"No {selected_category} models available for {selected_ram_range}")
 
+
 # Enhanced reference guide
 with st.expander("📘 Model Guide & Download Information"):
     st.markdown("""