fix(cache): satisfy strict typing budget

litellm/caching/in_memory_cache.py

@@ -210,7 +210,7 @@ class InMemoryCache(BaseCache):
         return False
 
     @staticmethod
-    def _copy_cached_value(value: Any) -> Any:
+    def _copy_cached_value(value: object) -> object:
         """Return a read-isolated value without making the cache brittle.
 
         In-memory cache entries can contain Pydantic models and mutable
@@ -227,7 +227,7 @@ class InMemoryCache(BaseCache):
         except Exception:  # noqa: BLE001 - cache reads must tolerate non-copyable values
             return value
 
-    def _get_cache_value(self, key, *, copy_value: bool) -> Any:
+    def _get_cache_value(self, key, *, copy_value: bool) -> object:
         if key in self.cache_dict:
             if self.evict_element_if_expired(key):
                 return None

tests/unit/caching/test_in_memory_cache.py

@@ -79,6 +79,19 @@ def test_in_memory_cache_returns_read_isolated_pydantic_models():
     assert stored.metadata == {"region": "us"}
 
 
+def test_in_memory_cache_preserves_non_copyable_mutable_values():
+    cache = InMemoryCache()
+    cache.set_cache("payload", ["unchanged"])
+
+    with patch(
+        "litellm.caching.in_memory_cache.copy.deepcopy",
+        side_effect=RuntimeError("not copyable"),
+    ):
+        cached = cache.get_cache("payload")
+
+    assert cached is cache.cache_dict["payload"]
+
+
 def test_in_memory_openai_obj_cache():
     from openai import OpenAI