diff --git a/docs/core_docs/docs/integrations/vectorstores/singlestore.mdx b/docs/core_docs/docs/integrations/vectorstores/singlestore.mdx
index 25e1462a92e8..451456f27623 100644
--- a/docs/core_docs/docs/integrations/vectorstores/singlestore.mdx
+++ b/docs/core_docs/docs/integrations/vectorstores/singlestore.mdx
@@ -64,7 +64,7 @@ If it is needed to filter results based on specific metadata fields, you can pas
### Vector indexes
Enhance your search efficiency with SingleStore DB version 8.5 or above by leveraging [ANN vector indexes](https://docs.singlestore.com/cloud/reference/sql-reference/vector-functions/vector-indexing/).
-By setting `useVectorIndex: true` during vector store object creation, you can activate this feature.
+By setting `useVectorIndex: true` during vector store object creation, you can activate this feature.
Additionally, if your vectors differ in dimensionality from the default OpenAI embedding size of 1536, ensure to specify the `vectorSize` parameter accordingly.
### Hybrid search
@@ -78,4 +78,4 @@ Notably, both `FILTER_BY_TEXT` and `FILTER_BY_VECTOR` necessitate a full-text in
These versatile strategies empower users to fine-tune searches according to their unique needs, facilitating efficient and precise data retrieval and analysis.
Moreover, SingleStoreDB's hybrid approaches, exemplified by `FILTER_BY_TEXT`, `FILTER_BY_VECTOR`, and `WEIGHTED_SUM` strategies, seamlessly blend vector and text-based searches to maximize efficiency and accuracy, ensuring users can fully leverage the platform's capabilities for a wide range of applications.
-{HybridSearchUsageExample}
\ No newline at end of file
+{HybridSearchUsageExample}