diff --git a/lightrag/operate.py b/lightrag/operate.py
index 468f4b2f..ec55694d 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -412,15 +412,17 @@ async def extract_entities(
     ):
         all_relationships_data.append(await result)
 
-    if not len(all_entities_data):
-        logger.warning("Didn't extract any entities, maybe your LLM is not working")
-        return None
-    if not len(all_relationships_data):
+    if not len(all_entities_data) and not len(all_relationships_data):
         logger.warning(
-            "Didn't extract any relationships, maybe your LLM is not working"
+            "Didn't extract any entities or relationships, maybe your LLM is not working"
         )
         return None
 
+    if not len(all_entities_data):
+        logger.warning("Didn't extract any entities")
+    if not len(all_relationships_data):
+        logger.warning("Didn't extract any relationships")
+
     if entity_vdb is not None:
         data_for_vdb = {
             compute_mdhash_id(dp["entity_name"], prefix="ent-"): {
@@ -630,6 +632,13 @@ async def _build_query_context(
                 text_chunks_db,
                 query_param,
             )
+            if (
+                hl_entities_context == ""
+                and hl_relations_context == ""
+                and hl_text_units_context == ""
+            ):
+                logger.warn("No high level context found. Switching to local mode.")
+                query_param.mode = "local"
     if query_param.mode == "hybrid":
         entities_context, relations_context, text_units_context = combine_contexts(
             [hl_entities_context, ll_entities_context],
@@ -865,7 +874,7 @@ async def _get_edge_data(
     results = await relationships_vdb.query(keywords, top_k=query_param.top_k)
 
     if not len(results):
-        return None
+        return "", "", ""
 
     edge_datas = await asyncio.gather(
         *[knowledge_graph_inst.get_edge(r["src_id"], r["tgt_id"]) for r in results]