From d0e5148a44ef4100a6c3daf16db927caa9f87ba0 Mon Sep 17 00:00:00 2001
From: zhgao <13942661420@163.com>
Date: Sat, 17 Oct 2026 11:20:42 +0800
Subject: [PATCH 1/2] Fix Cosmos MongoDB vector index kind set to similarity
 code

---
 python/semantic_kernel/connectors/azure_cosmos_db.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/python/semantic_kernel/connectors/azure_cosmos_db.py b/python/semantic_kernel/connectors/azure_cosmos_db.py
index 2d1bb53d9630..8e095b02c22c 100644
--- a/python/semantic_kernel/connectors/azure_cosmos_db.py
+++ b/python/semantic_kernel/connectors/azure_cosmos_db.py
@@ -399,7 +399,7 @@ def _get_index_definitions(self, **kwargs: Any) -> dict[str, Any]:
                     f"Distance function '{field.distance_function}' is not supported by Azure Cosmos DB for MongoDB."
                 )
             index_name = f"{field.storage_name or field.name}_"
-            index_kind = DISTANCE_FUNCTION_MAP_MONGODB[field.distance_function]
+            index_kind = INDEX_KIND_MAP_MONGODB[field.index_kind]
             index: dict[str, Any] = {
                 "name": index_name,
                 FieldTypes.KEY: {field.storage_name or field.name: "cosmosSearch"},

From 5d0e49edfa3ab07981d815c7375bbff21e891872 Mon Sep 17 00:00:00 2001
From: zhgao <13942661420@163.com>
Date: Sat, 17 Oct 2026 11:21:03 +0800
Subject: [PATCH 2/2] Correct index-kind test and add regression test for issue
 #14104

---
 ...test_azure_cosmos_db_mongodb_collection.py | 50 ++++++++++++++++++-
 1 file changed, 48 insertions(+), 2 deletions(-)

diff --git a/python/tests/unit/connectors/memory/azure_cosmos_db/test_azure_cosmos_db_mongodb_collection.py b/python/tests/unit/connectors/memory/azure_cosmos_db/test_azure_cosmos_db_mongodb_collection.py
index 8da8a1ab08e8..f41f1d59bc3d 100644
--- a/python/tests/unit/connectors/memory/azure_cosmos_db/test_azure_cosmos_db_mongodb_collection.py
+++ b/python/tests/unit/connectors/memory/azure_cosmos_db/test_azure_cosmos_db_mongodb_collection.py
@@ -98,8 +98,11 @@ async def test_ensure_collection_exists_calls_database_methods(definition) -> No
     # Check the vector field index creation
     assert command_args["indexes"][1]["name"] == "vector_"
     assert command_args["indexes"][1]["key"] == {"vector": "cosmosSearch"}
-    assert command_args["indexes"][1]["cosmosSearchOptions"]["kind"] == "COS"
-    assert command_args["indexes"][1]["cosmosSearchOptions"]["similarity"] is not None
+    # "kind" must be the index kind ("vector-hnsw" for index_kind="hnsw"),
+    # not the distance-function similarity code ("COS").
+    # See https://github.com/microsoft/semantic-kernel/issues/14104
+    assert command_args["indexes"][1]["cosmosSearchOptions"]["kind"] == "vector-hnsw"
+    assert command_args["indexes"][1]["cosmosSearchOptions"]["similarity"] == "COS"
     assert command_args["indexes"][1]["cosmosSearchOptions"]["dimensions"] == 5
 
 
@@ -154,3 +157,46 @@ async def test_context_manager_does_not_close_when_not_managed(mock_model) -> No
 
     # "__aexit__" should NOT call "close" when not managed
     external_client.close.assert_not_awaited()
+
+
+def test_get_index_definitions_uses_index_kind_for_kind() -> None:
+    """Regression test for https://github.com/microsoft/semantic-kernel/issues/14104.
+
+    The "kind" of a Cosmos DB for MongoDB vector index must come from
+    INDEX_KIND_MAP_MONGODB (e.g. "vector-hnsw"), not from the distance
+    function map ("COS"/"IP"/"L2"). Using the similarity code as "kind"
+    sends an invalid createIndexes command and also prevents the
+    HNSW/IVF/DiskANN tuning options from being attached (the `match`
+    block could never hit a "vector-*" case).
+    """
+    from semantic_kernel.data.vector import DistanceFunction, IndexKind
+
+    definition = VectorStoreCollectionDefinition(
+        fields=[
+            VectorStoreField("key", name="id"),
+            VectorStoreField("data", name="content"),
+            VectorStoreField(
+                "vector",
+                name="vector",
+                dimensions=4,
+                index_kind=IndexKind.HNSW,
+                distance_function=DistanceFunction.COSINE_SIMILARITY,
+            ),
+        ]
+    )
+    collection = CosmosMongoCollection(
+        collection_name="test_collection",
+        record_type=dict,
+        mongo_client=AsyncMock(spec=AsyncMongoClient),
+        definition=definition,
+    )
+
+    result = collection._get_index_definitions(m=16, efConstruction=64)
+    vector_index = next(i for i in result["indexes"] if "cosmosSearchOptions" in i)
+    options = vector_index["cosmosSearchOptions"]
+
+    assert options["kind"] == "vector-hnsw"
+    assert options["similarity"] == "COS"
+    assert options["dimensions"] == 4
+    assert options["m"] == 16
+    assert options["efConstruction"] == 64