fix(passthrough): bill streamed Responses calls that end incomplete

Streams that terminate with response.incomplete (e.g. max_output_tokens
reached) carry real usage in the terminal event but were rebuilt as None
and logged at zero spend, letting callers bypass budget enforcement.
Parse response.incomplete alongside response.completed when
reconstructing the streamed response.

litellm/llms/openai/responses/transformation.py

@@ -354,12 +354,13 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
             return event_pydantic_model.model_construct(**parsed_chunk)
 
     @staticmethod
-    def parse_completed_response_from_stream_chunks(all_chunks: list[str]) -> ResponsesAPIResponse | None:
+    def parse_terminal_response_from_stream_chunks(all_chunks: list[str]) -> ResponsesAPIResponse | None:
         for chunk_str in reversed(all_chunks):
-            try:
-                return ResponseCompletedEvent.model_validate_json(chunk_str.removeprefix("data: ")).response
-            except ValueError:
-                continue
+            for event_model in (ResponseCompletedEvent, ResponseIncompleteEvent):
+                try:
+                    return event_model.model_validate_json(chunk_str.removeprefix("data: ")).response
+                except ValueError:
+                    continue
         return None
 
     @staticmethod

litellm/proxy/pass_through_endpoints/llm_provider_handlers/openai_passthrough_logging_handler.py

@@ -542,7 +542,7 @@ class OpenAIPassthroughLoggingHandler(BasePassthroughLoggingHandler):
             handler: Final = OpenAIPassthroughLoggingHandler()
             handler_instance: Final = handler
             complete_response: Final = (
-                OpenAIResponsesAPIConfig.parse_completed_response_from_stream_chunks(all_chunks=all_chunks)
+                OpenAIResponsesAPIConfig.parse_terminal_response_from_stream_chunks(all_chunks=all_chunks)
                 if is_responses
                 else handler._build_complete_streaming_response(
                     all_chunks=all_chunks,

tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_openai_passthrough_logging_handler.py

@@ -593,6 +593,77 @@ class TestOpenAIPassthroughLoggingHandler:
             call_type="responses",
         )
 
+    @patch(f"{OpenAIPassthroughLoggingHandler.__module__}.get_standard_logging_object_payload")
+    @patch("litellm.completion_cost", return_value=2.1e-06)
+    def test_streaming_responses_incomplete_event_is_billed(self, mock_completion_cost, mock_get_standard_logging):
+        response_id = "resp_INCOMPLETESENTINEL0123456789ab"
+        incomplete_event = {
+            "type": "response.incomplete",
+            "sequence_number": 5,
+            "response": {
+                "id": response_id,
+                "object": "response",
+                "created_at": 1786374786,
+                "status": "incomplete",
+                "model": "gpt-4o-mini-2024-07-18",
+                "output": [
+                    {
+                        "id": "msg_abc",
+                        "type": "message",
+                        "status": "incomplete",
+                        "role": "assistant",
+                        "content": [
+                            {
+                                "type": "output_text",
+                                "text": "OK",
+                                "annotations": [],
+                            }
+                        ],
+                    }
+                ],
+                "usage": {
+                    "input_tokens": 14,
+                    "input_tokens_details": {"cached_tokens": 0},
+                    "output_tokens": 32,
+                    "output_tokens_details": {"reasoning_tokens": 0},
+                    "total_tokens": 46,
+                },
+                "error": None,
+                "incomplete_details": {"reason": "max_output_tokens"},
+                "instructions": None,
+                "metadata": {},
+                "parallel_tool_calls": True,
+                "temperature": 1.0,
+                "tool_choice": "auto",
+                "tools": [],
+                "top_p": 1.0,
+            },
+        }
+        logging_obj = self._create_mock_logging_obj()
+
+        result = OpenAIPassthroughLoggingHandler._handle_logging_openai_collected_chunks(
+            litellm_logging_obj=logging_obj,
+            passthrough_success_handler_obj=MagicMock(),
+            url_route="https://api.openai.com/v1/responses",
+            request_body={"model": "gpt-4o-mini", "stream": True},
+            endpoint_type=MagicMock(),
+            start_time=self.start_time,
+            all_chunks=[f"data: {json.dumps(incomplete_event)}"],
+            end_time=self.end_time,
+        )
+
+        response = result["result"]
+        assert response.id == response_id
+        assert response.status == "incomplete"
+        assert response.usage.output_tokens == 32
+        assert result["kwargs"]["response_cost"] == 2.1e-06
+        mock_completion_cost.assert_called_once_with(
+            completion_response=response,
+            model="gpt-4o-mini",
+            custom_llm_provider="openai",
+            call_type="responses",
+        )
+
     @patch(f"{OpenAIPassthroughLoggingHandler.__module__}.get_standard_logging_object_payload")
     @patch("litellm.completion_cost")
     def test_streaming_responses_without_completed_event_returns_none(