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2 changes: 1 addition & 1 deletion src/openai/lib/_parsing/_responses.py
Original file line number Diff line number Diff line change
Expand Up @@ -58,7 +58,7 @@ def parse_response(
) -> ParsedResponse[TextFormatT]:
output_list: List[ParsedResponseOutputItem[TextFormatT]] = []

for output in response.output:
for output in (response.output or []):
if output.type == "message":
content_list: List[ParsedContent[TextFormatT]] = []
for item in output.content:
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5 changes: 4 additions & 1 deletion src/openai/lib/streaming/responses/_responses.py
Original file line number Diff line number Diff line change
Expand Up @@ -357,9 +357,12 @@ def accumulate_event(self, event: RawResponseStreamEvent) -> ParsedResponseSnaps
if output.type == "function_call":
output.arguments += event.delta
elif event.type == "response.completed":
completed_response = event.response
if completed_response.output is None and snapshot.output is not None: # pyright: ignore[reportUnnecessaryComparison]
completed_response = completed_response.model_copy(update={"output": snapshot.output})
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P2 Badge Preserve Pydantic v1 compatibility when copying the response

In environments using Pydantic v1, which this package still supports via pydantic>=1.9.0, <3, Response instances do not have a model_copy method. When a streamed response.completed event has output: null and prior output items were accumulated, this fallback path will raise AttributeError before parsing, so the crash remains for supported Pydantic v1 users. Use the repository's compatibility helper or the v1 copy(update=...) path here.

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self._completed_response = parse_response(
text_format=self._text_format,
response=event.response,
response=completed_response,
input_tools=self._input_tools,
)

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113 changes: 113 additions & 0 deletions tests/lib/responses/test_null_output.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,113 @@
from __future__ import annotations

from openai._types import omit as _omit
from openai._models import construct_type_unchecked
from openai.types.responses import Response
from openai.lib._parsing._responses import parse_response
from openai.lib.streaming.responses._responses import ResponseStreamState
from openai.types.responses.response_stream_event import (
ResponseCreatedEvent,
ResponseCompletedEvent,
ResponseOutputItemAddedEvent,
)


def _make_response(**overrides: object) -> Response:
base = {
"id": "resp_1",
"object": "response",
"created_at": 1700000000.0,
"model": "gpt-5.2",
"output": [],
"status": "completed",
"parallel_tool_calls": True,
"tool_choice": "auto",
"tools": [],
"text": {"format": {"type": "text"}},
"truncation": "disabled",
}
base.update(overrides)
return construct_type_unchecked(type_=Response, value=base)


class TestParseResponseNullOutput:
def test_null_output_does_not_crash(self) -> None:
response = _make_response(output=None)
# Force output to None (bypassing Pydantic validation)
object.__setattr__(response, "output", None)

parsed = parse_response(
text_format=_omit,
input_tools=None,
response=response,
)
assert parsed.output == []

def test_empty_output_returns_empty(self) -> None:
response = _make_response(output=[])
parsed = parse_response(
text_format=_omit,
input_tools=None,
response=response,
)
assert parsed.output == []


class TestStreamAccumulatorSnapshotFallback:
def test_snapshot_fallback_when_completed_output_is_null(self) -> None:
state = ResponseStreamState(text_format=_omit, input_tools=[])

created_response = _make_response(output=[])
created_event = construct_type_unchecked(
type_=ResponseCreatedEvent,
value={
"type": "response.created",
"response": created_response.to_dict(),
"sequence_number": 0,
},
)
state.handle_event(created_event)

message_item = {
"id": "msg_1",
"type": "message",
"status": "completed",
"role": "assistant",
"content": [
{
"type": "output_text",
"text": "Hello world",
"annotations": [],
}
],
}
added_event = construct_type_unchecked(
type_=ResponseOutputItemAddedEvent,
value={
"type": "response.output_item.added",
"output_index": 0,
"item": message_item,
"sequence_number": 1,
},
)
state.handle_event(added_event)

completed_response_dict = created_response.to_dict()
completed_response_dict["output"] = None
completed_response_dict["status"] = "completed"

completed_event = construct_type_unchecked(
type_=ResponseCompletedEvent,
value={
"type": "response.completed",
"response": completed_response_dict,
"sequence_number": 2,
},
)
object.__setattr__(completed_event.response, "output", None)

state.handle_event(completed_event)

assert state._completed_response is not None
assert len(state._completed_response.output) == 1
assert state._completed_response.output[0].type == "message"