diff --git a/graphrag/api/query.py b/graphrag/api/query.py
index ae1438269b..dc11ee33c2 100644
--- a/graphrag/api/query.py
+++ b/graphrag/api/query.py
@@ -26,6 +26,7 @@
 
 from graphrag.config.embeddings import (
     community_full_content_embedding,
+    create_collection_name,
     entity_description_embedding,
     text_unit_text_embedding,
 )
@@ -47,7 +48,6 @@
     read_indexer_text_units,
 )
 from graphrag.utils.cli import redact
-from graphrag.utils.embeddings import create_collection_name
 from graphrag.vector_stores.base import BaseVectorStore
 from graphrag.vector_stores.factory import VectorStoreFactory
 
diff --git a/graphrag/config/embeddings.py b/graphrag/config/embeddings.py
index e63239ed6c..78f3cfdfe2 100644
--- a/graphrag/config/embeddings.py
+++ b/graphrag/config/embeddings.py
@@ -75,3 +75,22 @@ def get_embedding_settings(
     return {
         "strategy": strategy,
     }
+
+
+def create_collection_name(
+    container_name: str, embedding_name: str, validate: bool = True
+) -> str:
+    """
+    Create a collection name for the embedding store.
+
+    Within any given vector store, we can have multiple sets of embeddings organized into projects.
+    The `container` param is used for this partitioning, and is added as a prefix to the collection name for differentiation.
+
+    The embedding name is fixed, with the available list defined in graphrag.index.config.embeddings
+
+    Note that we use dot notation in our names, but many vector stores do not support this - so we convert to dashes.
+    """
+    if validate and embedding_name not in all_embeddings:
+        msg = f"Invalid embedding name: {embedding_name}"
+        raise KeyError(msg)
+    return f"{container_name}-{embedding_name}".replace(".", "-")
diff --git a/graphrag/index/operations/embed_text/embed_text.py b/graphrag/index/operations/embed_text/embed_text.py
index 79110c076d..c735d1024a 100644
--- a/graphrag/index/operations/embed_text/embed_text.py
+++ b/graphrag/index/operations/embed_text/embed_text.py
@@ -12,8 +12,8 @@
 
 from graphrag.cache.pipeline_cache import PipelineCache
 from graphrag.callbacks.workflow_callbacks import WorkflowCallbacks
+from graphrag.config.embeddings import create_collection_name
 from graphrag.index.operations.embed_text.strategies.typing import TextEmbeddingStrategy
-from graphrag.utils.embeddings import create_collection_name
 from graphrag.vector_stores.base import BaseVectorStore, VectorStoreDocument
 from graphrag.vector_stores.factory import VectorStoreFactory
 
diff --git a/graphrag/utils/embeddings.py b/graphrag/utils/embeddings.py
deleted file mode 100644
index ff9fb1cd3a..0000000000
--- a/graphrag/utils/embeddings.py
+++ /dev/null
@@ -1,25 +0,0 @@
-# Copyright (c) 2024 Microsoft Corporation.
-# Licensed under the MIT License
-
-"""Utilities for working with embeddings stores."""
-
-from graphrag.config.embeddings import all_embeddings
-
-
-def create_collection_name(
-    container_name: str, embedding_name: str, validate: bool = True
-) -> str:
-    """
-    Create a collection name for the embedding store.
-
-    Within any given vector store, we can have multiple sets of embeddings organized into projects.
-    The `container` param is used for this partitioning, and is added as a prefix to the collection name for differentiation.
-
-    The embedding name is fixed, with the available list defined in graphrag.index.config.embeddings
-
-    Note that we use dot notation in our names, but many vector stores do not support this - so we convert to dashes.
-    """
-    if validate and embedding_name not in all_embeddings:
-        msg = f"Invalid embedding name: {embedding_name}"
-        raise KeyError(msg)
-    return f"{container_name}-{embedding_name}".replace(".", "-")
diff --git a/tests/unit/utils/test_embeddings.py b/tests/unit/utils/test_embeddings.py
index 54a6b79647..854bf08180 100644
--- a/tests/unit/utils/test_embeddings.py
+++ b/tests/unit/utils/test_embeddings.py
@@ -3,7 +3,7 @@
 
 import pytest
 
-from graphrag.utils.embeddings import create_collection_name
+from graphrag.config.embeddings import create_collection_name
 
 
 def test_create_collection_name():