diff --git a/llama_stack/core/routers/__init__.py b/llama_stack/core/routers/__init__.py
index f851473c1..df4df0463 100644
--- a/llama_stack/core/routers/__init__.py
+++ b/llama_stack/core/routers/__init__.py
@@ -93,7 +93,7 @@ async def get_auto_router_impl(
         await inference_store.initialize()
         api_to_dep_impl["store"] = inference_store
 
-    if api == Api.vector_io and run_config.vector_stores:
+    elif api == Api.vector_io:
         api_to_dep_impl["vector_stores_config"] = run_config.vector_stores
 
     impl = api_to_routers[api.value](routing_table, **api_to_dep_impl)
diff --git a/llama_stack/core/routers/vector_io.py b/llama_stack/core/routers/vector_io.py
index e06d1d45c..bfc5f7164 100644
--- a/llama_stack/core/routers/vector_io.py
+++ b/llama_stack/core/routers/vector_io.py
@@ -31,6 +31,7 @@ from llama_stack.apis.vector_io import (
     VectorStoreObject,
     VectorStoreSearchResponsePage,
 )
+from llama_stack.core.datatypes import VectorStoresConfig
 from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import HealthResponse, HealthStatus, RoutingTable
 
@@ -43,7 +44,7 @@ class VectorIORouter(VectorIO):
     def __init__(
         self,
         routing_table: RoutingTable,
-        vector_stores_config=None,
+        vector_stores_config: VectorStoresConfig | None = None,
     ) -> None:
         logger.debug("Initializing VectorIORouter")
         self.routing_table = routing_table
@@ -125,12 +126,15 @@ class VectorIORouter(VectorIO):
         provider_id = extra.get("provider_id")
 
         # Use default embedding model if not specified
-        if embedding_model is None and self.vector_stores_config is not None:
-            if self.vector_stores_config.default_embedding_model is not None:
-                # Construct the full model ID with provider prefix
-                embedding_provider_id = self.vector_stores_config.default_embedding_model.provider_id
-                model_id = self.vector_stores_config.default_embedding_model.model_id
-                embedding_model = f"{embedding_provider_id}/{model_id}"
+        if (
+            embedding_model is None
+            and self.vector_stores_config
+            and self.vector_stores_config.default_embedding_model is not None
+        ):
+            # Construct the full model ID with provider prefix
+            embedding_provider_id = self.vector_stores_config.default_embedding_model.provider_id
+            model_id = self.vector_stores_config.default_embedding_model.model_id
+            embedding_model = f"{embedding_provider_id}/{model_id}"
 
         if embedding_model is not None and embedding_dimension is None:
             embedding_dimension = await self._get_embedding_model_dimension(embedding_model)