Convert parallel queries to serial execution

lightrag/kg/postgres_impl.py

@@ -142,6 +142,9 @@ class PostgreSQLDB:
         with_age: bool = False,
         graph_name: str | None = None,
     ) -> dict[str, Any] | None | list[dict[str, Any]]:
+        # start_time = time.time()
+        # logger.info(f"PostgreSQL, Querying:\n{sql}")
+
         async with self.pool.acquire() as connection:  # type: ignore
             if with_age and graph_name:
                 await self.configure_age(connection, graph_name)  # type: ignore
@@ -166,6 +169,11 @@ class PostgreSQLDB:
                         data = dict(zip(columns, rows[0]))
                     else:
                         data = None
+
+                # query_time = time.time() - start_time
+                # logger.info(f"PostgreSQL, Query result len: {len(data)}")
+                # logger.info(f"PostgreSQL, Query execution time: {query_time:.4f}s")
+
                 return data
             except Exception as e:
                 logger.error(f"PostgreSQL database, error:{e}")

lightrag/operate.py

@@ -1255,21 +1255,19 @@ async def _build_query_context(
             query_param,
         )
     else:  # hybrid mode
-        ll_data, hl_data = await asyncio.gather(
+        ll_data = await _get_node_data(
-            _get_node_data(
             ll_keywords,
             knowledge_graph_inst,
             entities_vdb,
             text_chunks_db,
             query_param,
-            ),
+        )
-            _get_edge_data(
+        hl_data = await _get_edge_data(
             hl_keywords,
             knowledge_graph_inst,
             relationships_vdb,
             text_chunks_db,
             query_param,
-            ),
         )
 
         (
@@ -1351,13 +1349,11 @@ async def _get_node_data(
         if n is not None
     ]  # what is this text_chunks_db doing.  dont remember it in airvx.  check the diagram.
     # get entitytext chunk
-    use_text_units, use_relations = await asyncio.gather(
+    use_text_units = await _find_most_related_text_unit_from_entities(
-        _find_most_related_text_unit_from_entities(
         node_datas, query_param, text_chunks_db, knowledge_graph_inst
-        ),
+    )
-        _find_most_related_edges_from_entities(
+    use_relations = await _find_most_related_edges_from_entities(
         node_datas, query_param, knowledge_graph_inst
-        ),
     )
 
     len_node_datas = len(node_datas)
@@ -1502,7 +1498,7 @@ async def _find_most_related_text_unit_from_entities(
                 all_text_units_lookup[c_id] = index
                 tasks.append((c_id, index, this_edges))
 
-    # Process in batches of 25 tasks at a time to avoid overwhelming resources
+    # Process in batches tasks at a time to avoid overwhelming resources
     batch_size = 5
     results = []