chore: tweak mapping and scoring

cognee/modules/graph/cognee_graph/CogneeGraph.py

@@ -241,12 +241,9 @@ class CogneeGraph(CogneeAbstractGraph):
         query_list_length: Optional[int] = None,
     ) -> None:
         """Map vector distances to nodes, supporting single- and multi-query input shapes."""
-        if not node_distances:
-            return None
 
         query_count = query_list_length or 1
 
-        # Reset all node distances for this search
         self.reset_distances(self.nodes.values(), query_count)
 
         for collection_name, scored_results in node_distances.items():
@@ -279,19 +276,17 @@ class CogneeGraph(CogneeAbstractGraph):
         query_list_length: Optional[int] = None,
     ) -> None:
         """Map vector distances to graph edges, supporting single- and multi-query input shapes."""
-        if not edge_distances:
-            return None
-
         query_count = query_list_length or 1
 
-        # Reset all edge distances for this search
         self.reset_distances(self.edges, query_count)
 
+        if not edge_distances:
+            return None
+
         per_query_edge_lists = self._normalize_query_distance_lists(
             edge_distances, query_list_length, "edge_distances"
         )
 
-        # For each query, apply distances to all matching edges
         for query_index, scored_list in enumerate(per_query_edge_lists):
             for result in scored_list:
                 payload = getattr(result, "payload", None)
@@ -318,13 +313,32 @@ class CogneeGraph(CogneeAbstractGraph):
     ) -> List[Edge]:
         """Calculate top k triplet importances for a specific query index."""
 
-        def score(edge):
+        def score(edge: Edge) -> float:
-            distances = [
+            elements = (
-                edge.node1.attributes.get("vector_distance"),
+                (edge.node1, f"node {edge.node1.id}"),
-                edge.node2.attributes.get("vector_distance"),
+                (edge.node2, f"node {edge.node2.id}"),
-                edge.attributes.get("vector_distance"),
+                (edge, f"edge {edge.node1.id}->{edge.node2.id}"),
-            ]
+            )
-            return sum(float(d[query_index]) for d in distances)
+
+            importances = []
+            for element, label in elements:
+                distances = element.attributes.get("vector_distance")
+                if not isinstance(distances, list) or query_index >= len(distances):
+                    raise ValueError(
+                        f"{label}: vector_distance must be a list with length > {query_index} "
+                        f"before scoring (got {type(distances).__name__} with length "
+                        f"{len(distances) if isinstance(distances, list) else 'n/a'})"
+                    )
+                value = distances[query_index]
+                try:
+                    importances.append(float(value))
+                except (TypeError, ValueError):
+                    raise ValueError(
+                        f"{label}: vector_distance[{query_index}] must be float-like, "
+                        f"got {type(value).__name__}"
+                    )
+
+            return sum(importances)
 
         return heapq.nsmallest(k, self.edges, key=score)
 

cognee/tests/unit/modules/graph/cognee_graph_test.py

@@ -614,7 +614,7 @@ async def test_calculate_top_triplet_importances_default_distances(setup_graph):
 
     # When no distances are set, calculate_top_triplet_importances should handle None
     # by either raising an error or skipping edges with None distances
-    with pytest.raises(TypeError, match="'NoneType' object is not subscriptable"):
+    with pytest.raises(ValueError):
         await graph.calculate_top_triplet_importances(k=1)
 
 
@@ -695,7 +695,7 @@ async def test_calculate_top_triplet_importances_raises_on_short_list(setup_grap
     edge.add_attribute("vector_distance", [0.3])
     graph.add_edge(edge)
 
-    with pytest.raises(IndexError):
+    with pytest.raises(ValueError):
         await graph.calculate_top_triplet_importances(k=1, query_list_length=2)
 
 
@@ -716,5 +716,5 @@ async def test_calculate_top_triplet_importances_raises_on_missing_attribute(set
     del edge.attributes["vector_distance"]
     graph.add_edge(edge)
 
-    with pytest.raises((KeyError, TypeError)):
+    with pytest.raises(ValueError):
         await graph.calculate_top_triplet_importances(k=1, query_list_length=1)