Update app.py

app.py

@@ -32,6 +32,15 @@ st.markdown("""
             border-radius: 12px;
             margin-bottom: 1rem;
         }
+         .stAlert {
+            background-color: #f0f0f5 !important;
+            color: #333333 !important;
+            padding: 1.25rem !important;
+            font-size: 1rem !important;
+            border-radius: 0.5rem !important;
+            box-shadow: 0 2px 5px rgba(0, 0, 0, 0.05) !important;
+        }
+            
     </style>
 """, unsafe_allow_html=True)
 
@@ -124,11 +133,11 @@ def is_valid_date(value):
         return False
 
 if not metadata_df.empty:
-    st.subheader("📦 Retrieved Metadata Sample")
+    st.subheader("Retrieved Metadata Sample")
     st.dataframe(metadata_df.head())
 
     # Metadata completeness analysis (enhanced)
-    st.subheader("🧠 Metadata Completeness Analysis")
+    st.subheader("Metadata Completeness Analysis")
     completeness = metadata_df.map(lambda x: not is_incomplete(x)).mean() * 100
     completeness_df = pd.DataFrame({"Field": completeness.index, "Completeness (%)": completeness.values})
     fig = px.bar(completeness_df, x="Field", y="Completeness (%)", title="Metadata Completeness by Field")
@@ -138,19 +147,19 @@ if not metadata_df.empty:
     incomplete_mask = metadata_df.map(is_incomplete).any(axis=1)
     incomplete_records = metadata_df[incomplete_mask]
 
-    st.subheader("⚠️ Records with Incomplete Metadata")
+    st.subheader("Records with Incomplete Metadata")
     if not incomplete_records.empty:
         st.dataframe(incomplete_records.astype(str))
     else:
         st.success("All metadata fields are complete in this collection!")
 
-    st.subheader("📌 Identifiers of Items Needing Metadata Updates")
+    st.subheader("Identifiers of Items Needing Metadata Updates")
     if not incomplete_records.empty:
         st.write(incomplete_records[['id', 'title']])
     else:
         st.success("All records are complete!")
 
-    st.subheader("✨ Suggested Metadata Enhancements")
+    st.subheader("Suggested Metadata Enhancements")
     filled_descriptions = metadata_df[metadata_df['description'].notnull()]['description'].astype(str)
     if len(filled_descriptions) > 1:
         try: