remove comments

api/core/rag/datasource/vdb/tencent/tencent_vector.py

@@ -156,14 +156,6 @@ def search_by_vector(self, query_vector: list[float], **kwargs: Any) -> list[Doc
         return self._get_search_res(res)
 
     def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
-        # res = (self._db.collection(self._collection_name)
-        #        .searchByText(embeddingItems=[query],
-        #                      params=document.HNSWSearchParams(ef=kwargs.get("ef", 10)),
-        #                      retrieve_vector=False,
-        #                      limit=kwargs.get('top_k', 4),
-        #                      timeout=self._client_config.timeout,
-        #                      ))
-        # must deploy embedding model in tencent vector db , for now not support
         return []
 
     def _get_search_res(self, res):