From 03e8dda8950f1a4bce004335860a52b430b8509c Mon Sep 17 00:00:00 2001
From: lspataroG <167472995+lspataroG@users.noreply.github.com>
Date: Tue, 17 Dec 2024 20:52:47 +0100
Subject: [PATCH] Test

---
 .../integration_tests/test_vectorstores.py    | 60 +++++++++----------
 1 file changed, 30 insertions(+), 30 deletions(-)

diff --git a/libs/vertexai/tests/integration_tests/test_vectorstores.py b/libs/vertexai/tests/integration_tests/test_vectorstores.py
index 6c3c4bbb..283ba292 100644
--- a/libs/vertexai/tests/integration_tests/test_vectorstores.py
+++ b/libs/vertexai/tests/integration_tests/test_vectorstores.py
@@ -298,36 +298,36 @@ def test_vector_store_hybrid_search(
         assert isinstance(scores["sparse_score"], float)
 
 
-@pytest.mark.extended
-@pytest.mark.parametrize(
-    "vector_store_class", ["vector_store", "datastore_vector_store"]
-)
-def test_add_texts_with_embeddings(
-    vector_store_class: str,
-    request: pytest.FixtureRequest,
-    embeddings: VertexAIEmbeddings,
-):
-    vector_store: VectorSearchVectorStore = request.getfixturevalue(vector_store_class)
-
-    texts = ["my favourite animal is the elephant", "my favourite animal is the lion"]
-    ids = ["idx1", "idx2"]
-    embs = embeddings.embed_documents(texts)
-    ids1 = vector_store.add_texts_with_embeddings(
-        texts=texts, embeddings=embs, ids=ids, is_complete_overwrite=True
-    )
-    assert len(ids1) == 2
-
-    sparse_embeddings: List[Dict[str, Union[List[int], List[float]]]] = [
-        {"values": [0.5, 0.7], "dimensions": [2, 4]}
-    ] * 2
-    ids2 = vector_store.add_texts_with_embeddings(
-        texts=texts,
-        embeddings=embs,
-        sparse_embeddings=sparse_embeddings,
-        ids=ids,
-        is_complete_overwrite=True,
-    )
-    assert ids == ids1 == ids2
+# @pytest.mark.extended
+# @pytest.mark.parametrize(
+#     "vector_store_class", ["vector_store", "datastore_vector_store"]
+# )
+# def test_add_texts_with_embeddings(
+#     vector_store_class: str,
+#     request: pytest.FixtureRequest,
+#     embeddings: VertexAIEmbeddings,
+# ):
+#     vector_store: VectorSearchVectorStore = request.getfixturevalue(vector_store_class)
+
+#     texts = ["my favourite animal is the elephant", "my favourite animal is the lion"]
+#     ids = ["idx1", "idx2"]
+#     embs = embeddings.embed_documents(texts)
+#     ids1 = vector_store.add_texts_with_embeddings(
+#         texts=texts, embeddings=embs, ids=ids, is_complete_overwrite=True
+#     )
+#     assert len(ids1) == 2
+
+#     sparse_embeddings: List[Dict[str, Union[List[int], List[float]]]] = [
+#         {"values": [0.5, 0.7], "dimensions": [2, 4]}
+#     ] * 2
+#     ids2 = vector_store.add_texts_with_embeddings(
+#         texts=texts,
+#         embeddings=embs,
+#         sparse_embeddings=sparse_embeddings,
+#         ids=ids,
+#         is_complete_overwrite=True,
+#     )
+#     assert ids == ids1 == ids2
 
 
 @pytest.mark.extended