TablestoreVectorStore check the Dimension of the embedding when writing it to store.

llama-index-integrations/vector_stores/llama-index-vector-stores-tablestore/llama_index/vector_stores/tablestore/base.py

@@ -54,6 +54,7 @@ class TablestoreVectorStore(BasePydanticVectorStore):
 
     is_embedding_query: bool = True
     stores_text: bool = True
+    _vector_dimension: int = PrivateAttr(default=512)
     _logger: Any = PrivateAttr(default=None)
     _tablestore_client: tablestore.OTSClient = PrivateAttr(default=None)
     _table_name: str = PrivateAttr(default="llama_index_vector_store_ots_v1")
@@ -91,6 +92,7 @@ def __init__(
             )
         else:
             self._tablestore_client = tablestore_client
+        self._vector_dimension = vector_dimension
         self._table_name = table_name
         self._index_name = index_name
         self._text_field = text_field
@@ -632,6 +634,11 @@ def add(self, nodes: List[BaseNode], **kwargs: Any) -> List[str]:
             return []
         ids = []
         for node in nodes:
+            if len(node.get_embedding()) != self._vector_dimension:
+                raise RuntimeError(
+                    "node embedding size:%d is not the same as vector store dim:%d"
+                    % (len(node.get_embedding()), self._vector_dimension)
+                )
             self._write_row(
                 row_id=node.node_id,
                 content=node.text,

llama-index-integrations/vector_stores/llama-index-vector-stores-tablestore/tests/test_vector_stores_tablestore.py

@@ -165,3 +165,27 @@ def test_tablestore() -> None:
     assert query_result.ids is not None
     assert query_result.similarities is not None
     assert query_result.similarities is not None
+
+
+def test_tablestore_add_dim() -> None:
+    store = TablestoreVectorStore(
+        endpoint="http://test.a.com",
+        instance_name="test",
+        access_key_id="test",
+        access_key_secret="test",
+        vector_dimension=512,
+        vector_metric_type=tablestore.VectorMetricType.VM_COSINE,
+    )
+    embedder = MockEmbedding(128)
+    node = TextNode(
+        id_="1",
+        text="hello world",
+        metadata={"type": "a", "time": 1995},
+    )
+    node.embedding = embedder.get_text_embedding(node.get_text())
+
+    try:
+        store.add([node])
+        raise RuntimeError("should failed")
+    except Exception as e:
+        assert "not the same as" in e.args[0]