Update src/streamlit_app.py

src/streamlit_app.py

@@ -34,7 +34,7 @@ os.environ["STREAMLIT_WATCHER_TYPE"] = "none"
 # Check if running on Streamlit Cloud vs locally
 is_streamlit_cloud = os.environ.get('STREAMLIT_RUNTIME_ENV') == 'cloud'
 MAX_ATOMS_CLOUD = 100  # Maximum atoms allowed on Streamlit Cloud
-MAX_ATOMS_CLOUD_UMA = 100
+MAX_ATOMS_CLOUD_UMA = 50
 
 # Set page configuration
 st.set_page_config(
@@ -484,7 +484,8 @@ st.markdown("---")
 with st.expander('## About This App'):
     # Show some information about the app
     st.write("""
-    This app allows you to perform atomistic simulations using pre-trained foundational machine learning interatomic potentials (MLIPs) such as those from the MACE and FairChem libraries.
+    Test, compare and benchmark universal machine learning interatomic potentials (MLIPs).
+    This app allows you to perform atomistic simulations using pre-trained foundational MLIPs such as those from the MACE and FairChem libraries.
     
     ### Features:
     - Upload structure files (XYZ, CIF, POSCAR, etc.) or select from examples