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Merge 7f13522143 into 22a349ee70

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nightcityblade 2026-08-27 19:48:11 -05:00 • committed by GitHub
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12
litellm/completion_extras/litellm_responses_transformation/transformation.py
View file

@ -1546,6 +1546,18 @@ class OpenAiResponsesToChatCompletionStreamIterator(BaseModelResponseIterator):
],
usage=usage,
)
elif event_type in ("response.failed", "error"):
failure_response_data = parsed_chunk.get("response") or {}
if not isinstance(failure_response_data, dict):
failure_response_data = {}
error_data = failure_response_data.get("error") or parsed_chunk.get("error") or parsed_chunk
error_message = error_data.get("message") if isinstance(error_data, dict) else None
raise litellm.APIError(
status_code=500,
message=error_message or "Responses API stream failed",
llm_provider="",
model=failure_response_data.get("model", ""),
)
else:
pass
# For any unhandled event types, create a minimal valid chunk or skip

31
tests/test_litellm/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py
View file

@ -21,6 +21,37 @@ if TYPE_CHECKING:
from litellm.types.utils import ModelResponse
@pytest.mark.parametrize(
("chunk", "message"),
[
(
{
"type": "response.failed",
"response": {
"model": "gpt-5.6-luna",
"error": {"code": "server_error", "message": "upstream failed"},
},
},
"upstream failed",
),
({"type": "error", "code": "server_error", "message": "stream failed"}, "stream failed"),
(
{"type": "response.failed", "response": "invalid", "error": {"message": "malformed failure"}},
"malformed failure",
),
],
)
def test_response_stream_failure_raises_api_error(chunk, message):
from litellm.completion_extras.litellm_responses_transformation.transformation import (
OpenAiResponsesToChatCompletionStreamIterator,
)
with pytest.raises(litellm.APIError, match=message) as exc_info:
OpenAiResponsesToChatCompletionStreamIterator.translate_responses_chunk_to_openai_stream(chunk)
assert exc_info.value.status_code == 500
def test_convert_chat_completion_messages_to_responses_api_image_input():
from litellm.completion_extras.litellm_responses_transformation.transformation import (
LiteLLMResponsesTransformationHandler,