Merge fe8949ca1c into 96096ea0ff

backend/app/services/graph_builder.py

@@ -233,6 +233,11 @@ class GraphBuilderService:
             annotations = {}
             
             for attr_def in entity_def.get("attributes", []):
+                # LLM may return attributes as strings instead of dicts
+                if isinstance(attr_def, str):
+                    attr_name = safe_attr_name(attr_def)
+                    attr_desc = attr_def
+                else:
                     attr_name = safe_attr_name(attr_def["name"])  # 使用安全名称
                     attr_desc = attr_def.get("description", attr_name)
                 # Zep API 需要 Field 的 description，这是必需的
@@ -257,6 +262,11 @@ class GraphBuilderService:
             annotations = {}
             
             for attr_def in edge_def.get("attributes", []):
+                # LLM may return attributes as strings instead of dicts
+                if isinstance(attr_def, str):
+                    attr_name = safe_attr_name(attr_def)
+                    attr_desc = attr_def
+                else:
                     attr_name = safe_attr_name(attr_def["name"])  # 使用安全名称
                     attr_desc = attr_def.get("description", attr_name)
                 # Zep API 需要 Field 的 description，这是必需的

backend/app/services/ontology_generator.py

@@ -298,6 +298,11 @@ class OntologyGenerator:
                 entity_name_map[original_name] = entity["name"]
             if "attributes" not in entity:
                 entity["attributes"] = []
+            # Normalize attributes: LLM may return strings instead of dicts
+            entity["attributes"] = [
+                attr if isinstance(attr, dict) else {"name": attr, "type": "text", "description": attr}
+                for attr in entity["attributes"]
+            ]
             if "examples" not in entity:
                 entity["examples"] = []
             # 确保description不超过100字符
@@ -322,6 +327,11 @@ class OntologyGenerator:
                 edge["source_targets"] = []
             if "attributes" not in edge:
                 edge["attributes"] = []
+            # Normalize attributes: LLM may return strings instead of dicts
+            edge["attributes"] = [
+                attr if isinstance(attr, dict) else {"name": attr, "type": "text", "description": attr}
+                for attr in edge["attributes"]
+            ]
             if len(edge.get("description", "")) > 100:
                 edge["description"] = edge["description"][:97] + "..."