Apply cosmetic changes and autoformat

cognee/modules/graph/utils/get_graph_from_model.py

@@ -1,11 +1,10 @@
 from datetime import datetime, timezone
+
 from cognee.infrastructure.engine import DataPoint
 from cognee.modules.storage.utils import copy_model
 
 
-def get_graph_from_model(
+def get_graph_from_model(data_point: DataPoint, added_nodes=None, added_edges=None):
-    data_point: DataPoint, added_nodes=None, added_edges=None
-):
 
     if not added_nodes:
         added_nodes = {}
@@ -24,7 +23,13 @@ def get_graph_from_model(
         elif isinstance(field_value, DataPoint):
             excluded_properties.add(field_name)
             nodes, edges, added_nodes, added_edges = add_nodes_and_edges(
-                data_point, field_name, field_value, nodes, edges, added_nodes, added_edges
+                data_point,
+                field_name,
+                field_value,
+                nodes,
+                edges,
+                added_nodes,
+                added_edges,
             )
 
         elif (
@@ -35,12 +40,13 @@ def get_graph_from_model(
             excluded_properties.add(field_name)
 
             for item in field_value:
+                n_edges_before = len(edges)
                 nodes, edges, added_nodes, added_edges = add_nodes_and_edges(
                     data_point, field_name, item, nodes, edges, added_nodes, added_edges
                 )
-                edges = [
+                edges = edges[:n_edges_before] + [
                     (*edge[:3], {**edge[3], "metadata": {"type": "list"}})
-                    for edge in edges
+                    for edge in edges[n_edges_before:]
                 ]
         else:
             data_point_properties[field_name] = field_value

cognee/modules/graph/utils/get_model_instance_from_graph.py

@@ -1,8 +1,12 @@
+from typing import Callable
+
 from pydantic_core import PydanticUndefined
+
 from cognee.infrastructure.engine import DataPoint
 from cognee.modules.storage.utils import copy_model
 
-def merge_dicts(dict1, dict2, agg_fn):
+
+def merge_dicts(dict1: dict, dict2: dict, agg_fn: Callable) -> dict:
     merged_dict = {}
     for key, value in dict1.items():
         if key in dict2:
@@ -15,22 +19,38 @@ def merge_dicts(dict1, dict2, agg_fn):
             merged_dict[key] = value
     return merged_dict
 
-def get_model_instance_from_graph(nodes: list[DataPoint], edges: list[tuple[str, str, str, dict[str, str]]], entity_id: str):
+
+def get_model_instance_from_graph(
+    nodes: list[DataPoint],
+    edges: list[tuple[str, str, str, dict[str, str]]],
+    entity_id: str,
+):
     node_map = {node.id: node for node in nodes}
 
     for source_node_id, target_node_id, edge_label, edge_properties in edges:
         source_node = node_map[source_node_id]
         target_node = node_map[target_node_id]
         edge_metadata = edge_properties.get("metadata", {})
-        edge_type = edge_metadata.get("type")
+        edge_type = edge_metadata.get("type", "default")
 
         if edge_type == "list":
-            NewModel = copy_model(type(source_node), { edge_label: (list[type(target_node)], PydanticUndefined) })
+            NewModel = copy_model(
-            new_model_dict = merge_dicts(source_node.model_dump(), { edge_label: [target_node] }, lambda a, b: a + b)
+                type(source_node),
+                {edge_label: (list[type(target_node)], PydanticUndefined)},
+            )
+            new_model_dict = merge_dicts(
+                source_node.model_dump(),
+                {edge_label: [target_node]},
+                lambda a, b: a + b,
+            )
             node_map[source_node_id] = NewModel(**new_model_dict)
         else:
-            NewModel = copy_model(type(source_node), { edge_label: (type(target_node), PydanticUndefined) })
+            NewModel = copy_model(
+                type(source_node), {edge_label: (type(target_node), PydanticUndefined)}
+            )
 
-            node_map[target_node_id] = NewModel(**source_node.model_dump(), **{ edge_label: target_node })
+            node_map[target_node_id] = NewModel(
+                **source_node.model_dump(), **{edge_label: target_node}
+            )
 
     return node_map[entity_id]

cognee/tests/unit/interfaces/graph/util.py

@@ -132,7 +132,6 @@ def count_society(obj):
 
 
 def show_first_difference(str1, str2, str1_name, str2_name, context=30):
-    """Shows where two strings first diverge, with surrounding context."""
     for i, (c1, c2) in enumerate(zip(str1, str2)):
         if c1 != c2:
             start = max(0, i - context)