diff --git a/rag/nlp/search.py b/rag/nlp/search.py
index f37ce24572..23e86cb9db 100644
--- a/rag/nlp/search.py
+++ b/rag/nlp/search.py
@@ -60,6 +60,58 @@ class Dealer:
         vector_column_name = f"q_{len(embedding_data)}_vec"
         return MatchDenseExpr(vector_column_name, embedding_data, 'float', 'cosine', topk, {"similarity": similarity})
 
+    async def _existing_doc_ids(self, doc_ids: list[str]) -> set[str]:
+        if not doc_ids:
+            return set()
+
+        unique_doc_ids = list(dict.fromkeys(doc_ids))
+
+        def _load():
+            from api.db.services.document_service import DocumentService
+
+            return {row["id"] for row in DocumentService.get_by_ids(unique_doc_ids).dicts()}
+
+        return await thread_pool_exec(_load)
+
+    async def _prune_deleted_chunks(self, sres: SearchResult) -> SearchResult:
+        chunk_doc_ids = [chunk.get("doc_id") for chunk in sres.field.values() if chunk and chunk.get("doc_id")]
+        if not chunk_doc_ids:
+            return sres
+
+        existing_doc_ids = await self._existing_doc_ids(chunk_doc_ids)
+        if len(existing_doc_ids) == len(set(chunk_doc_ids)):
+            return sres
+
+        filtered_ids = []
+        filtered_field = {}
+        filtered_highlight = {} if sres.highlight else sres.highlight
+        removed = 0
+
+        for chunk_id in sres.ids:
+            chunk = sres.field.get(chunk_id)
+            if not chunk or chunk.get("doc_id") not in existing_doc_ids:
+                removed += 1
+                continue
+
+            filtered_ids.append(chunk_id)
+            filtered_field[chunk_id] = chunk
+            if sres.highlight and chunk_id in sres.highlight:
+                filtered_highlight[chunk_id] = sres.highlight[chunk_id]
+
+        if removed:
+            logging.warning("Pruned %s stale chunks whose documents no longer exist.", removed)
+
+        return self.SearchResult(
+            total=len(filtered_ids),
+            ids=filtered_ids,
+            query_vector=sres.query_vector,
+            field=filtered_field,
+            highlight=filtered_highlight,
+            aggregation=sres.aggregation,
+            keywords=sres.keywords,
+            group_docs=sres.group_docs,
+        )
+
     def get_filters(self, req):
         condition = dict()
         for key, field in {"kb_ids": "kb_id", "doc_ids": "doc_id"}.items():
@@ -436,6 +488,10 @@ class Dealer:
 
         sres = await self.search(req, [index_name(tid) for tid in tenant_ids], kb_ids, embd_mdl, highlight,
                            rank_feature=rank_feature)
+        sres = await self._prune_deleted_chunks(sres)
+        if sres.total == 0:
+            ranks["doc_aggs"] = []
+            return ranks
 
         if rerank_mdl and sres.total > 0:
             sim, tsim, vsim = self.rerank_by_model(