diff --git a/libs/vertexai/langchain_google_vertexai/vectorstores/_utils.py b/libs/vertexai/langchain_google_vertexai/vectorstores/_utils.py
index 5538aaf1..fc6f7b77 100644
--- a/libs/vertexai/langchain_google_vertexai/vectorstores/_utils.py
+++ b/libs/vertexai/langchain_google_vertexai/vectorstores/_utils.py
@@ -1,5 +1,6 @@
 import json
 import uuid
+import warnings
 from typing import Any, Dict, List, Union
 
 from google.cloud.aiplatform import MatchingEngineIndex
@@ -81,6 +82,7 @@ def to_data_points(
         metadatas = [{}] * len(ids)
 
     data_points = []
+    ignored_fields = set()
 
     for id_, embedding, metadata in zip(ids, embeddings, metadatas):
         restricts = []
@@ -107,6 +109,15 @@ def to_data_points(
                     namespace=namespace, value_float=value
                 )
                 numeric_restricts.append(restriction)
+            else:
+                ignored_fields.add(namespace)
+
+        if len(ignored_fields) > 0:
+            warnings.warn(
+                f"Some values in fields {', '.join(ignored_fields)} are not usable for"
+                f" restrictions. In order to be used they must be str, list[str] or"
+                f" numeric."
+            )
 
         data_point = meidx_types.IndexDatapoint(
             datapoint_id=id_,
diff --git a/libs/vertexai/tests/unit_tests/test_vectorstores.py b/libs/vertexai/tests/unit_tests/test_vectorstores.py
new file mode 100644
index 00000000..9b1c30bc
--- /dev/null
+++ b/libs/vertexai/tests/unit_tests/test_vectorstores.py
@@ -0,0 +1,49 @@
+import pytest
+
+from langchain_google_vertexai.vectorstores._utils import to_data_points
+
+
+def test_to_data_points():
+    ids = ["Id1"]
+    embeddings = [[0.0, 0.0]]
+    metadatas = [
+        {
+            "some_string": "string",
+            "some_number": 1.1,
+            "some_list": ["a", "b"],
+            "some_random_object": {"foo": 1, "bar": 2},
+        }
+    ]
+
+    with pytest.warns():
+        result = to_data_points(ids, embeddings, metadatas)
+
+    assert isinstance(result, list)
+    assert len(result) == 1
+
+    datapoint = result[0]
+    datapoint.datapoint_id == "Id1"
+    for component_emb, component_fv in (datapoint.feature_vector, embeddings[0]):
+        assert component_emb == pytest.approx(component_fv)
+
+    metadata = metadatas[0]
+
+    restriction_lookup = {
+        restriction.namespace: restriction for restriction in datapoint.restricts
+    }
+
+    restriction = restriction_lookup.pop("some_string")
+    assert restriction.allow_list == [metadata["some_string"]]
+
+    restriction = restriction_lookup.pop("some_list")
+    assert restriction.allow_list == metadata["some_list"]
+
+    assert len(restriction_lookup) == 0
+
+    num_restriction_lookup = {
+        restriction.namespace: restriction
+        for restriction in datapoint.numeric_restricts
+    }
+    restriction = num_restriction_lookup.pop("some_number")
+    assert round(restriction.value_float, 1) == pytest.approx(metadata["some_number"])
+    assert len(num_restriction_lookup) == 0