Update app.py

app.py

@@ -115,10 +115,76 @@ st.markdown("""
         color: #E53E3E;
         font-weight: bold;
     }
+
+    /* Pariente AI Branding */
+    .pariente-ai {
+        color: #4A5568;
+        font-size: 0.875rem;
+        font-style: italic;
+        text-align: right;
+    }
+    .pariente-ai-footer {
+        background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+        -webkit-background-clip: text;
+        -webkit-text-fill-color: transparent;
+        font-weight: bold;
+    }
 </style>
 """, unsafe_allow_html=True)
 
-# Function to safely get value or return default
+# Function to extract IMO from Information field
+def extract_imo_from_info(info_text):
+    """Extract IMO number from Information field"""
+    import re
+    if not info_text or pd.isna(info_text):
+        return "N/A"
+    
+    # Look for IMO pattern: IMO- followed by 7 digits
+    imo_match = re.search(r'IMO-?\s*(\d{7})', str(info_text), re.IGNORECASE)
+    if imo_match:
+        return imo_match.group(1)
+    return "N/A"
+
+def extract_mmsi_from_info(info_text):
+    """Extract MMSI from Information field"""
+    import re
+    if not info_text or pd.isna(info_text):
+        return "N/A"
+    
+    # Look for MMSI pattern
+    mmsi_match = re.search(r'MMSI-?\s*(\d{9})', str(info_text), re.IGNORECASE)
+    if mmsi_match:
+        return mmsi_match.group(1)
+    return "N/A"
+
+def extract_call_sign_from_info(info_text):
+    """Extract Call Sign from Information field"""
+    import re
+    if not info_text or pd.isna(info_text):
+        return "N/A"
+    
+    # Look for Call Sign pattern
+    call_match = re.search(r'Call Sign-?\s*([A-Z0-9]+)', str(info_text), re.IGNORECASE)
+    if call_match:
+        return call_match.group(1)
+    return "N/A"
+
+def extract_owner_from_info(info_text):
+    """Extract owner information from Information field"""
+    import re
+    if not info_text or pd.isna(info_text):
+        return "N/A"
+    
+    # Look for Registered owner or Commercial manager
+    owner_match = re.search(r'Registered owner-?\s*([^,]+)', str(info_text), re.IGNORECASE)
+    if owner_match:
+        return owner_match.group(1).strip()
+    
+    manager_match = re.search(r'Commercial manager-?\s*([^,]+)', str(info_text), re.IGNORECASE)
+    if manager_match:
+        return manager_match.group(1).strip()
+    
+    return "N/A"
 def safe_get(row, key, default="N/A"):
     try:
         # Special handling for Name field
@@ -263,11 +329,14 @@ def create_sample_data():
     }
 
 # Header
-col1, col2 = st.columns([6, 1])
+col1, col2, col3 = st.columns([6, 1, 1])
 with col1:
     st.markdown("# 🛡️ Terror Finance & Maritime Watch")
+    st.markdown("*Powered by Pariente AI - Advanced Intelligence Analytics*")
 with col2:
     theme_toggle = st.checkbox("🌙", key="theme")
+with col3:
+    st.markdown('<div class="pariente-ai">🤖 <span class="pariente-ai-footer">Pariente AI</span><br><em>Intelligence Platform</em></div>', unsafe_allow_html=True)
 
 # Load data
 try:
@@ -536,7 +605,7 @@ with tab3:
             )
     
     # Filters for vessels
-    col1, col2, col3 = st.columns([3, 2, 2])
+    col1, col2, col3, col4 = st.columns([3, 2, 2, 2])
     
     with col1:
         name_filter = st.text_input("Search vessels", placeholder="Enter vessel name or IMO...", key="search_vessels")
@@ -555,6 +624,13 @@ with tab3:
             status_options += sorted([s for s in statuses if s and s.lower() != 'nan'])
         status_filter = st.selectbox("Status", status_options, key="status_vessels")
     
+    with col4:
+        org_options = ["All Organizations"]
+        if len(data['vessels']) > 0 and 'Linked To' in data['vessels'].columns:
+            orgs = data['vessels']['Linked To'].dropna().astype(str).unique()
+            org_options += sorted([o for o in orgs if o and o.lower() != 'nan'])
+        org_filter = st.selectbox("Organization", org_options, key="org_vessels")
+    
     # Apply filters
     filtered_vessels = data['vessels'].copy()
     
@@ -563,7 +639,8 @@ with tab3:
         mask = (
             filtered_vessels['Name'].str.contains(name_filter, case=False, na=False) |
             filtered_vessels.get('IMO', pd.Series()).astype(str).str.contains(name_filter, case=False, na=False) |
-            filtered_vessels.get('Owner', pd.Series()).astype(str).str.contains(name_filter, case=False, na=False)
+            filtered_vessels.get('Owner', pd.Series()).astype(str).str.contains(name_filter, case=False, na=False) |
+            filtered_vessels.get('Information', pd.Series()).astype(str).str.contains(name_filter, case=False, na=False)
         )
         filtered_vessels = filtered_vessels[mask]
     
@@ -576,6 +653,11 @@ with tab3:
         filtered_vessels = filtered_vessels[
             filtered_vessels['Status'] == status_filter
         ]
+    
+    if org_filter != "All Organizations":
+        filtered_vessels = filtered_vessels[
+            filtered_vessels['Linked To'] == org_filter
+        ]
 
     # Display vessels
     for _, vessel in filtered_vessels.iterrows():
@@ -699,6 +781,12 @@ with tab5:
 
 # Footer
 st.markdown("---")
-st.markdown("🛡️ **Terror Finance & Maritime Watch** - Monitoring entities involved in terror financing and maritime sanctions evasion")
-st.markdown(f"📊 Data processed: {len(data['individuals'])} individuals, {len(data['companies'])} companies, {len(data['vessels'])} vessels")
-st.markdown(f"🕒 Last updated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
+col1, col2 = st.columns([3, 1])
+with col1:
+    st.markdown("🛡️ **Terror Finance & Maritime Watch** - Monitoring entities involved in terror financing and maritime sanctions evasion")
+    st.markdown(f"📊 Data processed: {len(data['individuals'])} individuals, {len(data['companies'])} companies, {len(data['vessels'])} vessels")
+    st.markdown(f"🕒 Last updated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
+with col2:
+    st.markdown("**Powered by**")
+    st.markdown("🤖 **Pariente AI**")
+    st.markdown("*Advanced Intelligence Analytics*")