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fix(studio): handle empty Responses tool output (#6167)

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• fix: handle empty responses tool output

Normalize empty Responses `function_call_output.output` values before converting them into Chat Completions `role="tool"` messages. Empty strings, whitespace-only strings, and empty arrays now use the existing no-output sentinel, while non-empty text and content arrays are preserved.

Add regression coverage for empty tool outputs, image payloads outside `output`, content-array serialization, validator round trips, and preserving non-empty text.

---------

Co-authored-by: wasimysaid <wasimysdev@gmail.com>
Co-authored-by: Tai An <antai12232931@outlook.com>
Co-authored-by: Datta Nimmaturi <venkatadattasainimmaturi@gmail.com>
This commit is contained in:
Ritwij Aryan Parmar 2026-06-11 11:35:50 -04:00 • committed by GitHub
commit 181288e118
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GPG key ID: B5690EEEBB952194
2 changed files with 123 additions and 4 deletions
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18
studio/backend/routes/inference.py
View file

@ -4897,6 +4897,17 @@ def _responses_message_text(content: Union[str, list]) -> str:
return "\n".join(parts)
def _responses_tool_output_text(output: Union[str, list]) -> str:
"""Return Chat Completions-safe content for a Responses tool result."""
if isinstance(output, str):
return output if output.strip() else "(no output)"
if output:
return json.dumps(output)
return "(no output)"
def _normalise_responses_input(payload: ResponsesRequest) -> list[ChatMessage]:
"""Convert a ResponsesRequest's ``input`` into a Chat-format ``ChatMessage`` list.
@ -4956,10 +4967,9 @@ def _normalise_responses_input(payload: ResponsesRequest) -> list[ChatMessage]:
if isinstance(item, ResponsesFunctionCallOutputInputItem):
# Chat Completions `role="tool"` requires string content; serialize
# a Responses content-array output.
output = item.output
if not isinstance(output, str):
output = json.dumps(output)
# a Responses content-array output and keep empty outputs from
# tripping the stricter ChatMessage role validator.
output = _responses_tool_output_text(item.output)
messages.append(
ChatMessage(
role = "tool",

109
studio/backend/tests/test_responses_tool_passthrough.py
View file

@ -58,6 +58,7 @@ from routes.inference import (
_build_chat_request,
_chat_tool_calls_to_responses_output,
_normalise_responses_input,
_responses_tool_output_text,
_responses_stream,
_translate_responses_tool_choice_to_chat,
_translate_responses_tools_to_chat,
@ -393,6 +394,100 @@ class TestNormaliseResponsesInputWithTools:
# Content is serialised so llama-server sees a string.
assert json.loads(msgs[0].content) == [{"type": "output_text", "text": "ok"}]
def test_empty_function_call_output_gets_no_output_sentinel(self):
payload = ResponsesRequest(
input = [
{
"type": "function_call_output",
"call_id": "call_1",
"output": "",
}
],
)
msgs = _normalise_responses_input(payload)
assert msgs[0].role == "tool"
assert msgs[0].tool_call_id == "call_1"
assert msgs[0].content == "(no output)"
ChatMessage(**msgs[0].model_dump(exclude_none = True))
def test_whitespace_function_call_output_gets_no_output_sentinel(self):
payload = ResponsesRequest(
input = [
{
"type": "function_call_output",
"call_id": "call_1",
"output": " \n\t",
}
],
)
msgs = _normalise_responses_input(payload)
assert msgs[0].content == "(no output)"
def test_empty_content_array_output_gets_no_output_sentinel(self):
payload = ResponsesRequest(
input = [
{
"type": "function_call_output",
"call_id": "call_1",
"output": [],
}
],
)
msgs = _normalise_responses_input(payload)
assert msgs[0].content == "(no output)"
def test_image_content_array_tool_output_is_serialised(self):
payload = ResponsesRequest(
input = [
{
"type": "function_call_output",
"call_id": "call_1",
"output": [
{
"type": "image",
"source": {
"type": "base64",
"media_type": "image/png",
"data": "iVBORw0KGgo=",
},
}
],
}
],
)
msgs = _normalise_responses_input(payload)
assert msgs[0].role == "tool"
assert json.loads(msgs[0].content)[0]["type"] == "image"
def test_image_payload_outside_output_gets_no_output_sentinel(self):
payload = ResponsesRequest(
input = [
{
"type": "function_call_output",
"call_id": "call_1",
"output": "",
"content": [
{
"type": "image",
"source": {
"type": "base64",
"media_type": "image/png",
"data": "iVBORw0KGgo=",
},
}
],
}
],
)
msgs = _normalise_responses_input(payload)
assert msgs[0].role == "tool"
assert msgs[0].tool_call_id == "call_1"
assert msgs[0].content == "(no output)"
def test_tool_output_serializer_preserves_non_empty_text(self):
assert _responses_tool_output_text("done") == "done"
assert _responses_tool_output_text(" done ") == " done "
# =====================================================================
# Response mapping — tool_calls → function_call output items
@ -810,3 +905,17 @@ class TestTranslatedMessagesValidate:
# Building a fresh ChatMessage from the dump round-trips the
# role-shape validator — the passthrough's key invariant.
ChatMessage(**m.model_dump(exclude_none = True))
def test_empty_tool_output_round_trips_through_chat_message_validator(self):
payload = ResponsesRequest(
input = [
{
"type": "function_call_output",
"call_id": "call_empty",
"output": "",
},
],
)
msgs = _normalise_responses_input(payload)
for m in msgs:
ChatMessage(**m.model_dump(exclude_none = True))