test sync sagemaker calls

litellm/tests/test_sagemaker.py

@@ -44,19 +44,31 @@ def reset_callbacks():
 
 
 @pytest.mark.asyncio()
-async def test_completion_sagemaker():
+@pytest.mark.parametrize("sync_mode", [True, False])
+async def test_completion_sagemaker(sync_mode):
     try:
         litellm.set_verbose = True
         print("testing sagemaker")
-        response = await litellm.acompletion(
-            model="sagemaker/jumpstart-dft-hf-textgeneration1-mp-20240815-185614",
-            messages=[
-                {"role": "user", "content": "hi"},
-            ],
-            temperature=0.2,
-            max_tokens=80,
-            input_cost_per_second=0.000420,
-        )
+        if sync_mode is True:
+            response = litellm.completion(
+                model="sagemaker/jumpstart-dft-hf-textgeneration1-mp-20240815-185614",
+                messages=[
+                    {"role": "user", "content": "hi"},
+                ],
+                temperature=0.2,
+                max_tokens=80,
+                input_cost_per_second=0.000420,
+            )
+        else:
+            response = await litellm.acompletion(
+                model="sagemaker/jumpstart-dft-hf-textgeneration1-mp-20240815-185614",
+                messages=[
+                    {"role": "user", "content": "hi"},
+                ],
+                temperature=0.2,
+                max_tokens=80,
+                input_cost_per_second=0.000420,
+            )
         # Add any assertions here to check the response
         print(response)
         cost = completion_cost(completion_response=response)
@@ -125,3 +137,62 @@ async def test_acompletion_sagemaker_non_stream():
             kwargs["url"]
             == "https://runtime.sagemaker.us-west-2.amazonaws.com/endpoints/jumpstart-dft-hf-textgeneration1-mp-20240815-185614/invocations"
         )
+
+
+@pytest.mark.asyncio
+async def test_completion_sagemaker_non_stream():
+    mock_response = MagicMock()
+
+    def return_val():
+        return {
+            "generated_text": "This is a mock response from SageMaker.",
+            "id": "cmpl-mockid",
+            "object": "text_completion",
+            "created": 1629800000,
+            "model": "sagemaker/jumpstart-dft-hf-textgeneration1-mp-20240815-185614",
+            "choices": [
+                {
+                    "text": "This is a mock response from SageMaker.",
+                    "index": 0,
+                    "logprobs": None,
+                    "finish_reason": "length",
+                }
+            ],
+            "usage": {"prompt_tokens": 1, "completion_tokens": 8, "total_tokens": 9},
+        }
+
+    mock_response.json = return_val
+
+    expected_payload = {
+        "inputs": "hi",
+        "parameters": {"temperature": 0.2, "max_new_tokens": 80},
+    }
+
+    with patch(
+        "litellm.llms.custom_httpx.http_handler.HTTPHandler.post",
+        return_value=mock_response,
+    ) as mock_post:
+        # Act: Call the litellm.acompletion function
+        response = litellm.completion(
+            model="sagemaker/jumpstart-dft-hf-textgeneration1-mp-20240815-185614",
+            messages=[
+                {"role": "user", "content": "hi"},
+            ],
+            temperature=0.2,
+            max_tokens=80,
+            input_cost_per_second=0.000420,
+        )
+
+        # Print what was called on the mock
+        print("call args=", mock_post.call_args)
+
+        # Assert
+        mock_post.assert_called_once()
+        _, kwargs = mock_post.call_args
+        args_to_sagemaker = kwargs["json"]
+        print("Arguments passed to sagemaker=", args_to_sagemaker)
+        assert args_to_sagemaker == expected_payload
+        assert (
+            kwargs["url"]
+            == "https://runtime.sagemaker.us-west-2.amazonaws.com/endpoints/jumpstart-dft-hf-textgeneration1-mp-20240815-185614/invocations"
+        )