Update src/visualization.py

src/visualization.py

@@ -1206,114 +1206,101 @@ def display_graph_visualization(knowledge_graph, central_entity=None, max_distan
 
 def visualize_path(path_info, ontology_manager):
     """Visualize a semantic path between entities with enhanced graphics and details."""
+    import streamlit as st
+    import networkx as nx
+    import matplotlib.pyplot as plt
+    from collections import defaultdict
+
     if not path_info or "path" not in path_info:
         st.warning("No path information available.")
         return
-    
+
     st.subheader("🔄 Semantic Path Visualization")
-    
+
     path = path_info["path"]
-    
+
     # Get entity information for each node in the path
     entities = {}
     all_nodes = set()
-    
-    # Add source and target
+
     if "source" in path_info:
         source_id = path_info["source"]
         all_nodes.add(source_id)
         entities[source_id] = ontology_manager.get_entity_info(source_id)
-    
+
     if "target" in path_info:
         target_id = path_info["target"]
         all_nodes.add(target_id)
         entities[target_id] = ontology_manager.get_entity_info(target_id)
-    
-    # Add all entities in the path
+
     for edge in path:
         source_id = edge["source"]
         target_id = edge["target"]
         all_nodes.add(source_id)
         all_nodes.add(target_id)
-        
+
         if source_id not in entities:
             entities[source_id] = ontology_manager.get_entity_info(source_id)
-        
+
         if target_id not in entities:
             entities[target_id] = ontology_manager.get_entity_info(target_id)
-    
-    # Create tabs for different views
+
     tab1, tab2, tab3 = st.tabs(["Path Visualization", "Entity Details", "Path Summary"])
-    
+
     with tab1:
-        # Display path as a sequence diagram
-        display_path_visualization(path, entities)
-    
+        G = nx.DiGraph()
+        for edge in path:
+            G.add_edge(edge["source"], edge["target"], label=edge["type"])
+
+        pos = nx.spring_layout(G)
+        edge_labels = nx.get_edge_attributes(G, 'label')
+
+        fig, ax = plt.subplots()
+        nx.draw(G, pos, with_labels=True, node_color='lightblue', node_size=2000, font_size=10, ax=ax)
+        nx.draw_networkx_edge_labels(G, pos, edge_labels=edge_labels, font_color='red', ax=ax)
+        st.pyplot(fig)
+
     with tab2:
-        # Display details of entities in the path
         st.markdown("### Entities in Path")
-        
-        # Group entities by type
+
         entities_by_type = defaultdict(list)
         for entity_id in all_nodes:
             entity_info = entities.get(entity_id, {})
             entity_type = entity_info.get("class_type", entity_info.get("class", "Unknown"))
             entities_by_type[entity_type].append((entity_id, entity_info))
-        
-        # Create an expander for each entity type
+
         for entity_type, entity_list in entities_by_type.items():
-            with st.expander(f"{entity_type} ({len(entity_list)})", expanded=True):
-                for entity_id, entity_info in entity_list:
-                    st.markdown(f"**{entity_id}**")
-                    
-                    # Display properties if available
-                    if "properties" in entity_info and entity_info["properties"]:
-                        props_markdown = ", ".join([f"**{k}**: {v}" for k, v in entity_info["properties"].items()])
-                        st.markdown(props_markdown)
-                    
-                    st.markdown("---")
-    
+            st.subheader(f"{entity_type} ({len(entity_list)})")
+            for entity_id, entity_info in entity_list:
+                st.markdown(f"- **{entity_id}**")
+                for k, v in entity_info.get("properties", {}).items():
+                    st.markdown(f"  - {k}: {v}")
+            st.markdown("---")
+
     with tab3:
-        # Display textual summary of the path
         st.markdown("### Path Description")
-        
-        # If path_info has text, use it
         if "text" in path_info and path_info["text"]:
             st.markdown(f"**Path:** {path_info['text']}")
         else:
-            # Otherwise, generate a description
             path_steps = []
             for edge in path:
                 source_id = edge["source"]
                 target_id = edge["target"]
                 relation = edge["type"]
-                
-                # Get readable names if available
-                source_name = source_id
-                target_name = target_id
-                
-                if source_id in entities and "properties" in entities[source_id]:
-                    props = entities[source_id]["properties"]
-                    if "name" in props:
-                        source_name = props["name"]
-                
-                if target_id in entities and "properties" in entities[target_id]:
-                    props = entities[target_id]["properties"]
-                    if "name" in props:
-                        target_name = props["name"]
-                
+
+                source_name = entities[source_id].get("properties", {}).get("name", source_id)
+                target_name = entities[target_id].get("properties", {}).get("name", target_id)
+
                 path_steps.append(f"{source_name} **{relation}** {target_name}")
-            
+
             st.markdown(" → ".join(path_steps))
-        
-        # Display relevant business rules
+
         relevant_rules = find_relevant_rules_for_path(path, ontology_manager)
         if relevant_rules:
             st.markdown("### Relevant Business Rules")
             for rule in relevant_rules:
                 st.markdown(f"- **{rule['id']}**: {rule['description']}")
 
-
 def display_path_visualization(path, entities):
     """Create an enhanced visual representation of the path."""
     if not path: