def test_search_with_filter(self, node_embeddings: List[TextNode]) -> None:
        """Test end to end Vertex AI Vector Search with filter."""
        # Add nodes to the Vertex AI Vector Search index
        vector_store = self.vector_store()
        vector_store.add(node_embeddings)

        # similarity search
        embed_model = VertexTextEmbedding(project=PROJECT_ID, location=REGION)
        query = "I want some pants."
        query_embedding = embed_model.get_query_embedding(query)
        q = VectorStoreQuery(
            query_embedding=query_embedding,
            similarity_top_k=1,
            filters=MetadataFilters(
                filters=[MetadataFilter(key="color", value="blue")]
            ),
        )

        result = vector_store.query(q)
        assert result.nodes is not None and len(result.nodes) == 1
        assert result.nodes[0].metadata.get("color") == "blue"
Test end to end Vertex AI Vector Search with filter.
llama-index-integrations/vector_stores/llama-index-vector-stores-vertexaivectorsearch/tests/test_vector_stores_vertexaivectorsearch.py