diff --git a/libs/core/langchain_core/vectorstores/in_memory.py b/libs/core/langchain_core/vectorstores/in_memory.py
index eb37c6398fd..4f23910160c 100644
--- a/libs/core/langchain_core/vectorstores/in_memory.py
+++ b/libs/core/langchain_core/vectorstores/in_memory.py
@@ -21,9 +21,7 @@ from langchain_core.embeddings import Embeddings
 from langchain_core.load import dumpd, load
 from langchain_core.vectorstores import VectorStore
 from langchain_core.vectorstores.utils import _cosine_similarity as cosine_similarity
-from langchain_core.vectorstores.utils import (
-    _maximal_marginal_relevance as maximal_marginal_relevance,
-)
+from langchain_core.vectorstores.utils import maximal_marginal_relevance
 
 if TYPE_CHECKING:
     from langchain_core.indexing import UpsertResponse
diff --git a/libs/core/langchain_core/vectorstores/utils.py b/libs/core/langchain_core/vectorstores/utils.py
index 5bcf756747b..6655ab415f9 100644
--- a/libs/core/langchain_core/vectorstores/utils.py
+++ b/libs/core/langchain_core/vectorstores/utils.py
@@ -71,7 +71,7 @@ def _cosine_similarity(X: Matrix, Y: Matrix) -> np.ndarray:
         return similarity
 
 
-def _maximal_marginal_relevance(
+def maximal_marginal_relevance(
     query_embedding: np.ndarray,
     embedding_list: list,
     lambda_mult: float = 0.5,