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lightrag/kg/neo4j_impl.py

@@ -1058,7 +1058,7 @@ class Neo4JStorage(BaseGraphStorage):
         result = KnowledgeGraph()
         visited_nodes = set()
         visited_edges = set()
-        visited_edge_pairs = set()  # 用于跟踪已处理的边对(排序后的source_id, target_id)
+        visited_edge_pairs = set()  # Used to track processed edge pairs (sorted source_id, target_id)
 
         # Get the starting node's data
         async with self._driver.session(
@@ -1160,12 +1160,12 @@ class Neo4JStorage(BaseGraphStorage):
                                 properties=dict(rel),
                             )
 
-                            # 对source_id和target_id进行排序，确保(A,B)和(B,A)被视为同一条边
+                            # Sort source_id and target_id to ensure (A,B) and (B,A) are treated as the same edge
                             sorted_pair = tuple(sorted([current_node.id, target_id]))
 
-                            # 检查是否已存在相同的边（考虑无向性）
+                            # Check if the same edge already exists (considering undirectedness)
                             if sorted_pair not in visited_edge_pairs:
-                                # 只有当目标节点已经在结果中或将被添加到结果中时，才添加边
+                                # Only add the edge if the target node is already in the result or will be added
                                 if target_id in visited_nodes or (
                                     target_id not in visited_nodes
                                     and current_depth < max_depth

lightrag/kg/postgres_impl.py

@@ -1083,7 +1083,7 @@ class PGGraphStorage(BaseGraphStorage):
         if self.db is None:
             self.db = await ClientManager.get_client()
 
-        # 分别执行每个语句，忽略错误
+        # Execute each statement separately and ignore errors
         queries = [
             f"SELECT create_graph('{self.graph_name}')",
             f"SELECT create_vlabel('{self.graph_name}', 'base');",
@@ -2053,7 +2053,6 @@ class PGGraphStorage(BaseGraphStorage):
             KnowledgeGraph object containing nodes and edges, with an is_truncated flag
             indicating whether the graph was truncated due to max_nodes limit
         """
-        # 初始化 kg 变量，确保在所有情况下都有定义
         kg = KnowledgeGraph()
 
         # Handle wildcard query - get all nodes
@@ -2099,7 +2098,7 @@ class PGGraphStorage(BaseGraphStorage):
                 nodes_dict = {}
                 edges_dict = {}
                 for result in results:
-                    # 处理节点 a
+                    # Process node a
                     if result.get("a") and isinstance(result["a"], dict):
                         node_a = result["a"]
                         node_id = str(node_a["id"])
@@ -2110,7 +2109,7 @@ class PGGraphStorage(BaseGraphStorage):
                                 properties=node_a["properties"],
                             )
 
-                    # 处理节点 b
+                    # Process node b
                     if result.get("b") and isinstance(result["b"], dict):
                         node_b = result["b"]
                         node_id = str(node_b["id"])
@@ -2121,7 +2120,7 @@ class PGGraphStorage(BaseGraphStorage):
                                 properties=node_b["properties"],
                             )
 
-                    # 处理边 r
+                    # Process edge r
                     if result.get("r") and isinstance(result["r"], dict):
                         edge = result["r"]
                         edge_id = str(edge["id"])
@@ -2147,7 +2146,7 @@ class PGGraphStorage(BaseGraphStorage):
                 f"Subgraph query successful | Node count: {len(kg.nodes)} | Edge count: {len(kg.edges)}"
             )
         else:
-            # 非通配符查询，使用 BFS 算法
+            # For non-wildcard queries, use the BFS algorithm
             kg = await self._bfs_subgraph(node_label, max_depth, max_nodes)
             logger.info(
                 f"Subgraph query for '{node_label}' successful | Node count: {len(kg.nodes)} | Edge count: {len(kg.edges)}"