fix format

lightrag/kg/neo4j_impl.py

@@ -280,10 +280,7 @@ class Neo4JStorage(BaseGraphStorage):
                 MATCH (start:`{entity_name_label_source}`)-[r]->(end:`{entity_name_label_target}`)
                 RETURN properties(r) as edge_properties
                 LIMIT 1
-                """.format(
+                """
-                    entity_name_label_source=entity_name_label_source,
-                    entity_name_label_target=entity_name_label_target,
-                )
 
                 result = await session.run(query)
                 record = await result.single()

lightrag/operate.py

@@ -141,17 +141,18 @@ async def _handle_single_entity_extraction(
     if len(record_attributes) < 4 or record_attributes[0] != '"entity"':
         return None
     # add this record as a node in the G
-    entity_name = clean_str(record_attributes[1].upper())
+    entity_name = clean_str(record_attributes[1]).strip('"')
     if not entity_name.strip():
         return None
-    entity_type = clean_str(record_attributes[2].upper())
+    entity_type = clean_str(record_attributes[2]).strip('"')
-    entity_description = clean_str(record_attributes[3])
+    entity_description = clean_str(record_attributes[3]).strip('"')
     entity_source_id = chunk_key
     return dict(
         entity_name=entity_name,
         entity_type=entity_type,
         description=entity_description,
         source_id=entity_source_id,
+        metadata={"created_at": time.time()},
     )
 
 
@@ -162,14 +163,15 @@ async def _handle_single_relationship_extraction(
     if len(record_attributes) < 5 or record_attributes[0] != '"relationship"':
         return None
     # add this record as edge
-    source = clean_str(record_attributes[1].upper())
+    source = clean_str(record_attributes[1]).strip('"')
-    target = clean_str(record_attributes[2].upper())
+    target = clean_str(record_attributes[2]).strip('"')
-    edge_description = clean_str(record_attributes[3])
+    edge_description = clean_str(record_attributes[3]).strip('"')
-
+    edge_keywords = clean_str(record_attributes[4]).strip('"')
-    edge_keywords = clean_str(record_attributes[4])
     edge_source_id = chunk_key
     weight = (
-        float(record_attributes[-1]) if is_float_regex(record_attributes[-1]) else 1.0
+        float(record_attributes[-1].strip('"'))
+        if is_float_regex(record_attributes[-1])
+        else 1.0
     )
     return dict(
         src_id=source,
@@ -547,9 +549,13 @@ async def extract_entities(
     if entity_vdb is not None:
         data_for_vdb = {
             compute_mdhash_id(dp["entity_name"], prefix="ent-"): {
-                "content": dp["entity_name"] + dp["description"],
                 "entity_name": dp["entity_name"],
+                "entity_type": dp["entity_type"],
+                "content": f"{dp['entity_name']}\n{dp['description']}",
                 "source_id": dp["source_id"],
+                "metadata": {
+                    "created_at": dp.get("metadata", {}).get("created_at", time.time())
+                },
             }
             for dp in all_entities_data
         }
@@ -560,11 +566,9 @@ async def extract_entities(
             compute_mdhash_id(dp["src_id"] + dp["tgt_id"], prefix="rel-"): {
                 "src_id": dp["src_id"],
                 "tgt_id": dp["tgt_id"],
+                "keywords": dp["keywords"],
+                "content": f"{dp['src_id']}\t{dp['tgt_id']}\n{dp['keywords']}\n{dp['description']}",
                 "source_id": dp["source_id"],
-                "content": dp["keywords"]
-                + dp["src_id"]
-                + dp["tgt_id"]
-                + dp["description"],
                 "metadata": {
                     "created_at": dp.get("metadata", {}).get("created_at", time.time())
                 },
@@ -960,7 +964,7 @@ async def mix_kg_vector_query(
         stream=query_param.stream,
     )
 
-    # 清理响应内容
+    # Clean up response content
     if isinstance(response, str) and len(response) > len(sys_prompt):
         response = (
             response.replace(sys_prompt, "")
@@ -972,7 +976,7 @@ async def mix_kg_vector_query(
             .strip()
         )
 
-        # 7. Save cache - 只有在收集完整响应后才缓存
+        # 7. Save cache - Only cache after collecting complete response
         await save_to_cache(
             hashing_kv,
             CacheData(
@@ -1128,8 +1132,19 @@ async def _get_node_data(
     )
 
     # build prompt
-    entites_section_list = [["id", "entity", "type", "description", "rank"]]
+    entites_section_list = [
+        [
+            "id",
+            "entity",
+            "type",
+            "description",
+            "rank" "created_at",
+        ]
+    ]
     for i, n in enumerate(node_datas):
+        created_at = n.get("created_at", "UNKNOWN")
+        if isinstance(created_at, (int, float)):
+            created_at = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(created_at))
         entites_section_list.append(
             [
                 i,
@@ -1137,6 +1152,7 @@ async def _get_node_data(
                 n.get("entity_type", "UNKNOWN"),
                 n.get("description", "UNKNOWN"),
                 n["rank"],
+                created_at,
             ]
         )
     entities_context = list_of_list_to_csv(entites_section_list)
@@ -1401,6 +1417,10 @@ async def _get_edge_data(
 
     entites_section_list = [["id", "entity", "type", "description", "rank"]]
     for i, n in enumerate(use_entities):
+        created_at = e.get("created_at", "Unknown")
+        # Convert timestamp to readable format
+        if isinstance(created_at, (int, float)):
+            created_at = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(created_at))
         entites_section_list.append(
             [
                 i,
@@ -1408,6 +1428,7 @@ async def _get_edge_data(
                 n.get("entity_type", "UNKNOWN"),
                 n.get("description", "UNKNOWN"),
                 n["rank"],
+                created_at,
             ]
         )
     entities_context = list_of_list_to_csv(entites_section_list)
@@ -1766,6 +1787,8 @@ async def kg_query_with_keywords(
         system_prompt=sys_prompt,
         stream=query_param.stream,
     )
+
+    # 清理响应内容
     if isinstance(response, str) and len(response) > len(sys_prompt):
         response = (
             response.replace(sys_prompt, "")
@@ -1777,7 +1800,7 @@ async def kg_query_with_keywords(
             .strip()
         )
 
-    # Save to cache
+        # 7. Save cache - 只有在收集完整响应后才缓存
         await save_to_cache(
             hashing_kv,
             CacheData(
@@ -1791,4 +1814,5 @@ async def kg_query_with_keywords(
                 cache_type="query",
             ),
         )
+
     return response