refactor: cleanup duplicates

litellm/tests/test_lowest_latency_routing.py

@@ -54,8 +54,10 @@ def test_latency_updated():
         == test_cache.get_cache(key=latency_key)[deployment_id]["latency"][0]
     )
 
+
 # test_tpm_rpm_updated()
 
+
 def test_latency_updated_custom_ttl():
     """
     Invalidate the cached request.
@@ -95,45 +97,6 @@ def test_latency_updated_custom_ttl():
     assert test_cache.get_cache(key=latency_key) is None
 
 
-def test_latency_updated_custom_ttl():
-    """
-    Invalidate the cached request.
-
-    Test that the cache is empty
-    """
-    test_cache = DualCache()
-    model_list = []
-    cache_time = 3
-    lowest_latency_logger = LowestLatencyLoggingHandler(
-        router_cache=test_cache, model_list=model_list, routing_args={"ttl": cache_time}
-    )
-    model_group = "gpt-3.5-turbo"
-    deployment_id = "1234"
-    kwargs = {
-        "litellm_params": {
-            "metadata": {
-                "model_group": "gpt-3.5-turbo",
-                "deployment": "azure/chatgpt-v-2",
-            },
-            "model_info": {"id": deployment_id},
-        }
-    }
-    start_time = time.time()
-    response_obj = {"usage": {"total_tokens": 50}}
-    time.sleep(5)
-    end_time = time.time()
-    lowest_latency_logger.log_success_event(
-        response_obj=response_obj,
-        kwargs=kwargs,
-        start_time=start_time,
-        end_time=end_time,
-    )
-    latency_key = f"{model_group}_map"
-    assert isinstance(test_cache.get_cache(key=latency_key), dict)
-    time.sleep(cache_time)
-    assert test_cache.get_cache(key=latency_key) is None
-
-
 def test_get_available_deployments():
     test_cache = DualCache()
     model_list = [