diff --git a/lightrag/operate.py b/lightrag/operate.py
index feaec27d..45c9ef16 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -990,23 +990,37 @@ async def _find_related_text_unit_from_relationships(
     for index, unit_list in enumerate(text_units):
         for c_id in unit_list:
             if c_id not in all_text_units_lookup:
-                all_text_units_lookup[c_id] = {
-                    "data": await text_chunks_db.get_by_id(c_id),
-                    "order": index,
-                }
+                chunk_data = await text_chunks_db.get_by_id(c_id)
+                # Only store valid data
+                if chunk_data is not None and "content" in chunk_data:
+                    all_text_units_lookup[c_id] = {
+                        "data": chunk_data,
+                        "order": index,
+                    }
 
-    if any([v is None for v in all_text_units_lookup.values()]):
-        logger.warning("Text chunks are missing, maybe the storage is damaged")
-    all_text_units = [
-        {"id": k, **v} for k, v in all_text_units_lookup.items() if v is not None
-    ]
+    if not all_text_units_lookup:
+        logger.warning("No valid text chunks found")
+        return []
+
+    all_text_units = [{"id": k, **v} for k, v in all_text_units_lookup.items()]
     all_text_units = sorted(all_text_units, key=lambda x: x["order"])
-    all_text_units = truncate_list_by_token_size(
-        all_text_units,
+
+    # Ensure all text chunks have content
+    valid_text_units = [
+        t for t in all_text_units if t["data"] is not None and "content" in t["data"]
+    ]
+
+    if not valid_text_units:
+        logger.warning("No valid text chunks after filtering")
+        return []
+
+    truncated_text_units = truncate_list_by_token_size(
+        valid_text_units,
         key=lambda x: x["data"]["content"],
         max_token_size=query_param.max_token_for_text_unit,
     )
-    all_text_units: list[TextChunkSchema] = [t["data"] for t in all_text_units]
+
+    all_text_units: list[TextChunkSchema] = [t["data"] for t in truncated_text_units]
 
     return all_text_units
 
@@ -1050,24 +1064,43 @@ async def naive_query(
     results = await chunks_vdb.query(query, top_k=query_param.top_k)
     if not len(results):
         return PROMPTS["fail_response"]
+
     chunks_ids = [r["id"] for r in results]
     chunks = await text_chunks_db.get_by_ids(chunks_ids)
 
+    # Filter out invalid chunks
+    valid_chunks = [
+        chunk for chunk in chunks if chunk is not None and "content" in chunk
+    ]
+
+    if not valid_chunks:
+        logger.warning("No valid chunks found after filtering")
+        return PROMPTS["fail_response"]
+
     maybe_trun_chunks = truncate_list_by_token_size(
-        chunks,
+        valid_chunks,
         key=lambda x: x["content"],
         max_token_size=query_param.max_token_for_text_unit,
     )
+
+    if not maybe_trun_chunks:
+        logger.warning("No chunks left after truncation")
+        return PROMPTS["fail_response"]
+
     logger.info(f"Truncate {len(chunks)} to {len(maybe_trun_chunks)} chunks")
     section = "\n--New Chunk--\n".join([c["content"] for c in maybe_trun_chunks])
+
     if query_param.only_need_context:
         return section
+
     sys_prompt_temp = PROMPTS["naive_rag_response"]
     sys_prompt = sys_prompt_temp.format(
         content_data=section, response_type=query_param.response_type
     )
+
     if query_param.only_need_prompt:
         return sys_prompt
+
     response = await use_model_func(
         query,
         system_prompt=sys_prompt,