diff --git a/api/core/rag/datasource/vdb/oceanbase/oceanbase_vector.py b/api/core/rag/datasource/vdb/oceanbase/oceanbase_vector.py index 288b4819dc..ea843ef5b2 100644 --- a/api/core/rag/datasource/vdb/oceanbase/oceanbase_vector.py +++ b/api/core/rag/datasource/vdb/oceanbase/oceanbase_vector.py @@ -112,13 +112,13 @@ class OceanBaseVector(BaseVector): params=DEFAULT_OCEANBASE_HNSW_BUILD_PARAM, ) - fts_idxs: Optional[list[FtsIndexParam]] + fts_idxs: Optional[list[FtsIndexParam]] = None if self._hybrid_search_enabled: - fts_idxs = [FtsIndexParam(index_name="fulltext_index_for_col_text", - field_names=["text"], - parser_type=FtsParser.IK)] - else: - fts_idxs = None + fts_idxs = [ + FtsIndexParam( + index_name="fulltext_index_for_col_text", field_names=["text"], parser_type=FtsParser.IK + ) + ] self._client.create_table_with_index_params( table_name=self._collection_name, @@ -155,15 +155,13 @@ class OceanBaseVector(BaseVector): batch_size = 100 for i in range(0, len(ids), batch_size): - batch_ids = ids[i:i + batch_size] - batch_docs = documents[i:i + batch_size] - batch_embs = embeddings[i:i + batch_size] - batch_data = [{ - "id": id, - "vector": emb, - "text": doc.page_content, - "metadata": doc.metadata - } for id, doc, emb in zip(batch_ids, batch_docs, batch_embs)] + batch_ids = ids[i : i + batch_size] + batch_docs = documents[i : i + batch_size] + batch_embs = embeddings[i : i + batch_size] + batch_data = [ + {"id": id, "vector": emb, "text": doc.page_content, "metadata": doc.metadata} + for id, doc, emb in zip(batch_ids, batch_docs, batch_embs) + ] self._client.insert( table_name=self._collection_name,