diff --git a/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py b/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py index a2849ab91a2..ccece8018ff 100644 --- a/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py +++ b/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py @@ -817,3 +817,181 @@ class TestOpenAIResponsesHandlerToolCallExtraction: assert task_mappings[0] == (0, 0) assert task_mappings[1] == (0, 1) assert task_mappings[2] == (0, 2) + + +class MockPassThroughGuardrail(CustomGuardrail): + """Mock guardrail that passes through without blocking - for testing streaming fallback behavior""" + + async def apply_guardrail( + self, + inputs: GenericGuardrailAPIInputs, + request_data: dict, + input_type: Literal["request", "response"], + logging_obj: Optional[Any] = None, + ) -> GenericGuardrailAPIInputs: + """Simply return inputs unchanged""" + return inputs + + +class TestOpenAIResponsesHandlerStreamingOutputProcessing: + """Test streaming output processing functionality""" + + @pytest.mark.asyncio + async def test_process_output_streaming_response_empty_output(self): + """Test that streaming response with empty output doesn't raise IndexError + + This test verifies the fix for the bug where accessing model_response_choices[0] + would raise IndexError when the response.completed event has an empty output array. + """ + handler = OpenAIResponsesHandler() + guardrail = MockPassThroughGuardrail(guardrail_name="test") + + # Simulate a response.completed streaming event with empty output + responses_so_far = [ + { + "type": "response.completed", + "response": { + "id": "resp_123", + "output": [], # Empty output - this was causing the IndexError + "status": "completed", + }, + } + ] + + # This should not raise IndexError + result = await handler.process_output_streaming_response( + responses_so_far=responses_so_far, + guardrail_to_apply=guardrail, + litellm_logging_obj=None, + ) + + # Should return the responses unchanged + assert result == responses_so_far + + @pytest.mark.asyncio + async def test_process_output_streaming_response_missing_output_key(self): + """Test that streaming response with missing output key doesn't raise IndexError + + This test verifies the handler gracefully handles when the response dict + doesn't contain an 'output' key at all. + """ + handler = OpenAIResponsesHandler() + guardrail = MockPassThroughGuardrail(guardrail_name="test") + + # Simulate a response.completed streaming event with missing output key + responses_so_far = [ + { + "type": "response.completed", + "response": { + "id": "resp_123", + "status": "completed", + # No 'output' key - get() will return [] + }, + } + ] + + # This should not raise IndexError + result = await handler.process_output_streaming_response( + responses_so_far=responses_so_far, + guardrail_to_apply=guardrail, + litellm_logging_obj=None, + ) + + # Should return the responses unchanged + assert result == responses_so_far + + @pytest.mark.asyncio + async def test_process_output_streaming_response_unrecognized_output_type(self): + """Test that streaming response with unrecognized output types doesn't raise IndexError + + This test verifies the handler gracefully handles when output items are of + unrecognized types that _convert_response_output_to_choices skips over. + """ + handler = OpenAIResponsesHandler() + guardrail = MockPassThroughGuardrail(guardrail_name="test") + + # Simulate a response.completed streaming event with unrecognized output type + responses_so_far = [ + { + "type": "response.completed", + "response": { + "id": "resp_123", + "output": [ + { + "type": "unknown_type", # Unrecognized type + "id": "item_123", + "data": "some data", + } + ], + "status": "completed", + }, + } + ] + + # This should not raise IndexError + result = await handler.process_output_streaming_response( + responses_so_far=responses_so_far, + guardrail_to_apply=guardrail, + litellm_logging_obj=None, + ) + + # Should return the responses unchanged + assert result == responses_so_far + + @pytest.mark.asyncio + async def test_process_output_streaming_response_with_valid_output(self): + """Test that streaming response with valid output still works correctly""" + handler = OpenAIResponsesHandler() + guardrail = MockPassThroughGuardrail(guardrail_name="test") + + # Simulate a response.completed streaming event with valid message output + responses_so_far = [ + { + "type": "response.created", + "response": {"id": "resp_123"}, + }, + { + "type": "response.output_item.added", + "item": {"type": "message", "id": "msg_123"}, + }, + { + "type": "response.content_part.added", + "part": {"type": "output_text", "text": ""}, + }, + { + "type": "response.output_text.delta", + "delta": "Hello", + }, + { + "type": "response.output_text.delta", + "delta": " world", + }, + { + "type": "response.completed", + "response": { + "id": "resp_123", + "output": [ + { + "type": "message", + "id": "msg_123", + "status": "completed", + "role": "assistant", + "content": [ + {"type": "output_text", "text": "Hello world"}, + ], + } + ], + "status": "completed", + }, + }, + ] + + # This should process successfully + result = await handler.process_output_streaming_response( + responses_so_far=responses_so_far, + guardrail_to_apply=guardrail, + litellm_logging_obj=None, + ) + + # Should return the responses + assert result == responses_so_far