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feat(responses)!: add in_progress, failed, content part events (#3765)

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## Summary
- add schema + runtime support for response.in_progress /
response.failed / response.incomplete
- stream content parts with proper indexes and reasoning slots
- align tests + docs with the richer event payloads

## Testing
- uv run pytest
tests/unit/providers/agents/meta_reference/test_openai_responses.py::test_create_openai_response_with_string_input
- uv run pytest
tests/unit/providers/agents/meta_reference/test_response_conversion_utils.py
This commit is contained in:
Ashwin Bharambe 2025-10-10 07:27:34 -07:00 • committed by GitHub
parent a548169b99
commit e039b61d26
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12 changed files with 1431 additions and 221 deletions
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178
tests/unit/providers/agents/meta_reference/test_openai_responses.py
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@ -156,9 +156,10 @@ async def test_create_openai_response_with_string_input(openai_responses_impl, m
)
# Should have content part events for text streaming
# Expected: response.created, content_part.added, output_text.delta, content_part.done, response.completed
assert len(chunks) >= 4
# Expected: response.created, response.in_progress, content_part.added, output_text.delta, content_part.done, response.completed
assert len(chunks) >= 5
assert chunks[0].type == "response.created"
assert any(chunk.type == "response.in_progress" for chunk in chunks)
# Check for content part events
content_part_added_events = [c for c in chunks if c.type == "response.content_part.added"]
@ -169,6 +170,14 @@ async def test_create_openai_response_with_string_input(openai_responses_impl, m
assert len(content_part_done_events) >= 1, "Should have content_part.done event for text"
assert len(text_delta_events) >= 1, "Should have text delta events"
added_event = content_part_added_events[0]
done_event = content_part_done_events[0]
assert added_event.content_index == 0
assert done_event.content_index == 0
assert added_event.output_index == done_event.output_index == 0
assert added_event.item_id == done_event.item_id
assert added_event.response_id == done_event.response_id
# Verify final event is completion
assert chunks[-1].type == "response.completed"
@ -177,6 +186,8 @@ async def test_create_openai_response_with_string_input(openai_responses_impl, m
assert final_response.model == model
assert len(final_response.output) == 1
assert isinstance(final_response.output[0], OpenAIResponseMessage)
assert final_response.output[0].id == added_event.item_id
assert final_response.id == added_event.response_id
openai_responses_impl.responses_store.store_response_object.assert_called_once()
assert final_response.output[0].content[0].text == "Dublin"
@ -303,9 +314,20 @@ async def test_create_openai_response_with_tool_call_type_none(openai_responses_
chunks = [chunk async for chunk in result]
# Verify event types
# Should have: response.created, output_item.added, function_call_arguments.delta,
# function_call_arguments.done, output_item.done, response.completed
assert len(chunks) == 6
# Should have: response.created, response.in_progress, output_item.added,
# function_call_arguments.delta, function_call_arguments.done, output_item.done, response.completed
assert len(chunks) == 7
event_types = [chunk.type for chunk in chunks]
assert event_types == [
"response.created",
"response.in_progress",
"response.output_item.added",
"response.function_call_arguments.delta",
"response.function_call_arguments.done",
"response.output_item.done",
"response.completed",
]
# Verify inference API was called correctly (after iterating over result)
first_call = mock_inference_api.openai_chat_completion.call_args_list[0]
@ -314,25 +336,19 @@ async def test_create_openai_response_with_tool_call_type_none(openai_responses_
assert first_call.kwargs["temperature"] == 0.1
# Check response.created event (should have empty output)
assert chunks[0].type == "response.created"
assert len(chunks[0].response.output) == 0
# Check streaming events
assert chunks[1].type == "response.output_item.added"
assert chunks[2].type == "response.function_call_arguments.delta"
assert chunks[3].type == "response.function_call_arguments.done"
assert chunks[4].type == "response.output_item.done"
# Check response.completed event (should have the tool call)
assert chunks[5].type == "response.completed"
assert len(chunks[5].response.output) == 1
assert chunks[5].response.output[0].type == "function_call"
assert chunks[5].response.output[0].name == "get_weather"
completed_chunk = chunks[-1]
assert completed_chunk.type == "response.completed"
assert len(completed_chunk.response.output) == 1
assert completed_chunk.response.output[0].type == "function_call"
assert completed_chunk.response.output[0].name == "get_weather"
async def test_create_openai_response_with_tool_call_function_arguments_none(openai_responses_impl, mock_inference_api):
"""Test creating an OpenAI response with a tool call response that has a function that does not accept arguments, or arguments set to None when they are not mandatory."""
# Setup
"""Test creating an OpenAI response with tool calls that omit arguments."""
input_text = "What is the time right now?"
model = "meta-llama/Llama-3.1-8B-Instruct"
@ -359,9 +375,21 @@ async def test_create_openai_response_with_tool_call_function_arguments_none(ope
object="chat.completion.chunk",
)
mock_inference_api.openai_chat_completion.return_value = fake_stream_toolcall()
def assert_common_expectations(chunks) -> None:
first_call = mock_inference_api.openai_chat_completion.call_args_list[0]
assert first_call.kwargs["messages"][0].content == input_text
assert first_call.kwargs["tools"] is not None
assert first_call.kwargs["temperature"] == 0.1
assert len(chunks[0].response.output) == 0
completed_chunk = chunks[-1]
assert completed_chunk.type == "response.completed"
assert len(completed_chunk.response.output) == 1
assert completed_chunk.response.output[0].type == "function_call"
assert completed_chunk.response.output[0].name == "get_current_time"
assert completed_chunk.response.output[0].arguments == "{}"
# Function does not accept arguments
mock_inference_api.openai_chat_completion.return_value = fake_stream_toolcall()
result = await openai_responses_impl.create_openai_response(
input=input_text,
model=model,
@ -369,46 +397,23 @@ async def test_create_openai_response_with_tool_call_function_arguments_none(ope
temperature=0.1,
tools=[
OpenAIResponseInputToolFunction(
name="get_current_time",
description="Get current time for system's timezone",
parameters={},
name="get_current_time", description="Get current time for system's timezone", parameters={}
)
],
)
# Check that we got the content from our mocked tool execution result
chunks = [chunk async for chunk in result]
# Verify event types
# Should have: response.created, output_item.added, function_call_arguments.delta,
# function_call_arguments.done, output_item.done, response.completed
assert len(chunks) == 5
# Verify inference API was called correctly (after iterating over result)
first_call = mock_inference_api.openai_chat_completion.call_args_list[0]
assert first_call.kwargs["messages"][0].content == input_text
assert first_call.kwargs["tools"] is not None
assert first_call.kwargs["temperature"] == 0.1
# Check response.created event (should have empty output)
assert chunks[0].type == "response.created"
assert len(chunks[0].response.output) == 0
# Check streaming events
assert chunks[1].type == "response.output_item.added"
assert chunks[2].type == "response.function_call_arguments.done"
assert chunks[3].type == "response.output_item.done"
# Check response.completed event (should have the tool call with arguments set to "{}")
assert chunks[4].type == "response.completed"
assert len(chunks[4].response.output) == 1
assert chunks[4].response.output[0].type == "function_call"
assert chunks[4].response.output[0].name == "get_current_time"
assert chunks[4].response.output[0].arguments == "{}"
mock_inference_api.openai_chat_completion.return_value = fake_stream_toolcall()
assert [chunk.type for chunk in chunks] == [
"response.created",
"response.in_progress",
"response.output_item.added",
"response.function_call_arguments.done",
"response.output_item.done",
"response.completed",
]
assert_common_expectations(chunks)
# Function accepts optional arguments
mock_inference_api.openai_chat_completion.return_value = fake_stream_toolcall()
result = await openai_responses_impl.create_openai_response(
input=input_text,
model=model,
@ -418,42 +423,47 @@ async def test_create_openai_response_with_tool_call_function_arguments_none(ope
OpenAIResponseInputToolFunction(
name="get_current_time",
description="Get current time for system's timezone",
parameters={
"timezone": "string",
},
parameters={"timezone": "string"},
)
],
)
# Check that we got the content from our mocked tool execution result
chunks = [chunk async for chunk in result]
assert [chunk.type for chunk in chunks] == [
"response.created",
"response.in_progress",
"response.output_item.added",
"response.function_call_arguments.done",
"response.output_item.done",
"response.completed",
]
assert_common_expectations(chunks)
# Verify event types
# Should have: response.created, output_item.added, function_call_arguments.delta,
# function_call_arguments.done, output_item.done, response.completed
assert len(chunks) == 5
# Verify inference API was called correctly (after iterating over result)
first_call = mock_inference_api.openai_chat_completion.call_args_list[0]
assert first_call.kwargs["messages"][0].content == input_text
assert first_call.kwargs["tools"] is not None
assert first_call.kwargs["temperature"] == 0.1
# Check response.created event (should have empty output)
assert chunks[0].type == "response.created"
assert len(chunks[0].response.output) == 0
# Check streaming events
assert chunks[1].type == "response.output_item.added"
assert chunks[2].type == "response.function_call_arguments.done"
assert chunks[3].type == "response.output_item.done"
# Check response.completed event (should have the tool call with arguments set to "{}")
assert chunks[4].type == "response.completed"
assert len(chunks[4].response.output) == 1
assert chunks[4].response.output[0].type == "function_call"
assert chunks[4].response.output[0].name == "get_current_time"
assert chunks[4].response.output[0].arguments == "{}"
# Function accepts optional arguments with additional optional fields
mock_inference_api.openai_chat_completion.return_value = fake_stream_toolcall()
result = await openai_responses_impl.create_openai_response(
input=input_text,
model=model,
stream=True,
temperature=0.1,
tools=[
OpenAIResponseInputToolFunction(
name="get_current_time",
description="Get current time for system's timezone",
parameters={"timezone": "string", "location": "string"},
)
],
)
chunks = [chunk async for chunk in result]
assert [chunk.type for chunk in chunks] == [
"response.created",
"response.in_progress",
"response.output_item.added",
"response.function_call_arguments.done",
"response.output_item.done",
"response.completed",
]
assert_common_expectations(chunks)
mock_inference_api.openai_chat_completion.return_value = fake_stream_toolcall()
async def test_create_openai_response_with_multiple_messages(openai_responses_impl, mock_inference_api):