561 lines
20 KiB
Python
561 lines
20 KiB
Python
# SPDX-License-Identifier: Apache-2.0
|
|
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
|
|
|
|
import pytest
|
|
from openai.types.chat import ChatCompletionMessageParam
|
|
from openai.types.responses.response_function_tool_call import ResponseFunctionToolCall
|
|
from openai.types.responses.response_function_tool_call_output_item import (
|
|
ResponseFunctionToolCallOutputItem,
|
|
)
|
|
from openai.types.responses.response_output_message import ResponseOutputMessage
|
|
from openai.types.responses.response_output_text import ResponseOutputText
|
|
from openai.types.responses.response_reasoning_item import (
|
|
Content,
|
|
ResponseReasoningItem,
|
|
Summary,
|
|
)
|
|
|
|
from vllm.entrypoints.constants import MCP_PREFIX
|
|
from vllm.entrypoints.openai.responses.utils import (
|
|
_construct_single_message_from_response_item,
|
|
_maybe_combine_reasoning_and_tool_call,
|
|
construct_chat_messages_with_tool_call,
|
|
convert_tool_responses_to_completions_format,
|
|
should_continue_final_message,
|
|
)
|
|
|
|
|
|
class TestResponsesUtils:
|
|
"""Tests for convert_tool_responses_to_completions_format function."""
|
|
|
|
def test_convert_tool_responses_to_completions_format(self):
|
|
"""Test basic conversion of a flat tool schema to nested format."""
|
|
input_tool = {
|
|
"type": "function",
|
|
"name": "get_weather",
|
|
"description": "Get the current weather in a given location",
|
|
"parameters": {
|
|
"type": "object",
|
|
"properties": {
|
|
"location": {"type": "string"},
|
|
"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
|
|
},
|
|
"required": ["location", "unit"],
|
|
},
|
|
}
|
|
|
|
result = convert_tool_responses_to_completions_format(input_tool)
|
|
|
|
assert result == {"type": "function", "function": input_tool}
|
|
|
|
def test_construct_chat_messages_with_tool_call(self):
|
|
"""Test construction of chat messages with tool calls."""
|
|
reasoning_item = ResponseReasoningItem(
|
|
id="lol",
|
|
summary=[],
|
|
type="reasoning",
|
|
content=[
|
|
Content(
|
|
text="Leroy Jenkins",
|
|
type="reasoning_text",
|
|
)
|
|
],
|
|
encrypted_content=None,
|
|
status=None,
|
|
)
|
|
mcp_tool_item = ResponseFunctionToolCall(
|
|
id="mcp_123",
|
|
call_id="call_123",
|
|
type="function_call",
|
|
status="completed",
|
|
name="python",
|
|
arguments='{"code": "123+456"}',
|
|
)
|
|
input_items = [reasoning_item, mcp_tool_item]
|
|
messages = construct_chat_messages_with_tool_call(input_items)
|
|
|
|
assert len(messages) == 1
|
|
message = messages[0]
|
|
assert message["role"] == "assistant"
|
|
assert message["reasoning"] == "Leroy Jenkins"
|
|
assert message["tool_calls"][0]["id"] == "call_123"
|
|
assert message["tool_calls"][0]["function"]["name"] == "python"
|
|
assert (
|
|
message["tool_calls"][0]["function"]["arguments"] == '{"code": "123+456"}'
|
|
)
|
|
|
|
def test_construct_single_message_from_response_item(self):
|
|
item = ResponseReasoningItem(
|
|
id="lol",
|
|
summary=[],
|
|
type="reasoning",
|
|
content=[
|
|
Content(
|
|
text="Leroy Jenkins",
|
|
type="reasoning_text",
|
|
)
|
|
],
|
|
encrypted_content=None,
|
|
status=None,
|
|
)
|
|
formatted_item = _construct_single_message_from_response_item(item)
|
|
assert formatted_item["role"] == "assistant"
|
|
assert formatted_item["reasoning"] == "Leroy Jenkins"
|
|
|
|
item = ResponseReasoningItem(
|
|
id="lol",
|
|
summary=[
|
|
Summary(
|
|
text='Hmm, the user has just started with a simple "Hello,"',
|
|
type="summary_text",
|
|
)
|
|
],
|
|
type="reasoning",
|
|
content=None,
|
|
encrypted_content=None,
|
|
status=None,
|
|
)
|
|
|
|
formatted_item = _construct_single_message_from_response_item(item)
|
|
assert formatted_item["role"] == "assistant"
|
|
assert (
|
|
formatted_item["reasoning"]
|
|
== 'Hmm, the user has just started with a simple "Hello,"'
|
|
)
|
|
|
|
tool_call_output = ResponseFunctionToolCallOutputItem(
|
|
id="temp_id",
|
|
type="function_call_output",
|
|
call_id="temp",
|
|
output="1234",
|
|
status="completed",
|
|
)
|
|
formatted_item = _construct_single_message_from_response_item(tool_call_output)
|
|
assert formatted_item["role"] == "tool"
|
|
assert formatted_item["content"] == "1234"
|
|
assert formatted_item["tool_call_id"] == "temp"
|
|
|
|
item = ResponseReasoningItem(
|
|
id="lol",
|
|
summary=[],
|
|
type="reasoning",
|
|
content=None,
|
|
encrypted_content="TOP_SECRET_MESSAGE",
|
|
status=None,
|
|
)
|
|
with pytest.raises(ValueError):
|
|
_construct_single_message_from_response_item(item)
|
|
|
|
output_item = ResponseOutputMessage(
|
|
id="msg_bf585bbbe3d500e0",
|
|
content=[
|
|
ResponseOutputText(
|
|
annotations=[],
|
|
text="dongyi",
|
|
type="output_text",
|
|
logprobs=None,
|
|
)
|
|
],
|
|
role="assistant",
|
|
status="completed",
|
|
type="message",
|
|
)
|
|
|
|
formatted_item = _construct_single_message_from_response_item(output_item)
|
|
assert formatted_item["role"] == "assistant"
|
|
assert formatted_item["content"] == "dongyi"
|
|
|
|
|
|
class TestShouldContinueFinalMessage:
|
|
"""Tests for should_continue_final_message function.
|
|
|
|
This function enables Anthropic-style partial message completion, where
|
|
users can provide an incomplete assistant message and have the model
|
|
continue from where it left off.
|
|
"""
|
|
|
|
def test_string_input_returns_false(self):
|
|
"""String input is always a user message, so should not continue."""
|
|
assert should_continue_final_message("Hello, world!") is False
|
|
|
|
def test_empty_list_returns_false(self):
|
|
"""Empty list should not continue."""
|
|
assert should_continue_final_message([]) is False
|
|
|
|
def test_completed_message_returns_false(self):
|
|
"""Completed message should not be continued."""
|
|
output_item = ResponseOutputMessage(
|
|
id="msg_123",
|
|
content=[
|
|
ResponseOutputText(
|
|
annotations=[],
|
|
text="The answer is 42.",
|
|
type="output_text",
|
|
logprobs=None,
|
|
)
|
|
],
|
|
role="assistant",
|
|
status="completed",
|
|
type="message",
|
|
)
|
|
assert should_continue_final_message([output_item]) is False
|
|
|
|
def test_in_progress_message_returns_true(self):
|
|
"""In-progress message should be continued.
|
|
|
|
This is the key use case for partial message completion.
|
|
Example: The user provides "The best answer is (" and wants
|
|
the model to continue from there.
|
|
"""
|
|
output_item = ResponseOutputMessage(
|
|
id="msg_123",
|
|
content=[
|
|
ResponseOutputText(
|
|
annotations=[],
|
|
text="The best answer is (",
|
|
type="output_text",
|
|
logprobs=None,
|
|
)
|
|
],
|
|
role="assistant",
|
|
status="in_progress",
|
|
type="message",
|
|
)
|
|
assert should_continue_final_message([output_item]) is True
|
|
|
|
def test_incomplete_message_returns_true(self):
|
|
"""Incomplete message should be continued."""
|
|
output_item = ResponseOutputMessage(
|
|
id="msg_123",
|
|
content=[
|
|
ResponseOutputText(
|
|
annotations=[],
|
|
text="The answer",
|
|
type="output_text",
|
|
logprobs=None,
|
|
)
|
|
],
|
|
role="assistant",
|
|
status="incomplete",
|
|
type="message",
|
|
)
|
|
assert should_continue_final_message([output_item]) is True
|
|
|
|
def test_in_progress_reasoning_returns_true(self):
|
|
"""In-progress reasoning should be continued."""
|
|
reasoning_item = ResponseReasoningItem(
|
|
id="reasoning_123",
|
|
summary=[],
|
|
type="reasoning",
|
|
content=[
|
|
Content(
|
|
text="Let me think about this...",
|
|
type="reasoning_text",
|
|
)
|
|
],
|
|
encrypted_content=None,
|
|
status="in_progress",
|
|
)
|
|
assert should_continue_final_message([reasoning_item]) is True
|
|
|
|
def test_incomplete_reasoning_returns_true(self):
|
|
"""Incomplete reasoning should be continued."""
|
|
reasoning_item = ResponseReasoningItem(
|
|
id="reasoning_123",
|
|
summary=[],
|
|
type="reasoning",
|
|
content=[
|
|
Content(
|
|
text="Let me think",
|
|
type="reasoning_text",
|
|
)
|
|
],
|
|
encrypted_content=None,
|
|
status="incomplete",
|
|
)
|
|
assert should_continue_final_message([reasoning_item]) is True
|
|
|
|
reasoning_item = {
|
|
"id": "reasoning_123",
|
|
"summary": [],
|
|
"type": "reasoning",
|
|
"content": [],
|
|
"status": "incomplete",
|
|
}
|
|
assert should_continue_final_message([reasoning_item]) is True
|
|
|
|
def test_completed_reasoning_returns_false(self):
|
|
"""Completed reasoning should not be continued."""
|
|
reasoning_item = ResponseReasoningItem(
|
|
id="reasoning_123",
|
|
summary=[],
|
|
type="reasoning",
|
|
content=[
|
|
Content(
|
|
text="I have thought about this.",
|
|
type="reasoning_text",
|
|
)
|
|
],
|
|
encrypted_content=None,
|
|
status="completed",
|
|
)
|
|
assert should_continue_final_message([reasoning_item]) is False
|
|
|
|
def test_reasoning_with_none_status_returns_false(self):
|
|
"""Reasoning with None status should not be continued."""
|
|
reasoning_item = ResponseReasoningItem(
|
|
id="reasoning_123",
|
|
summary=[],
|
|
type="reasoning",
|
|
content=[
|
|
Content(
|
|
text="Some reasoning",
|
|
type="reasoning_text",
|
|
)
|
|
],
|
|
encrypted_content=None,
|
|
status=None,
|
|
)
|
|
assert should_continue_final_message([reasoning_item]) is False
|
|
|
|
def test_only_last_item_matters(self):
|
|
"""Only the last item in the list determines continuation."""
|
|
completed_item = ResponseOutputMessage(
|
|
id="msg_1",
|
|
content=[
|
|
ResponseOutputText(
|
|
annotations=[],
|
|
text="Complete message.",
|
|
type="output_text",
|
|
logprobs=None,
|
|
)
|
|
],
|
|
role="assistant",
|
|
status="completed",
|
|
type="message",
|
|
)
|
|
in_progress_item = ResponseOutputMessage(
|
|
id="msg_2",
|
|
content=[
|
|
ResponseOutputText(
|
|
annotations=[],
|
|
text="Partial message...",
|
|
type="output_text",
|
|
logprobs=None,
|
|
)
|
|
],
|
|
role="assistant",
|
|
status="in_progress",
|
|
type="message",
|
|
)
|
|
|
|
# In-progress as last item -> should continue
|
|
assert should_continue_final_message([completed_item, in_progress_item]) is True
|
|
|
|
# Completed as last item -> should not continue
|
|
assert (
|
|
should_continue_final_message([in_progress_item, completed_item]) is False
|
|
)
|
|
|
|
def test_tool_call_returns_false(self):
|
|
"""Tool calls should not trigger continuation."""
|
|
tool_call = ResponseFunctionToolCall(
|
|
id="fc_123",
|
|
call_id="call_123",
|
|
type="function_call",
|
|
status="in_progress",
|
|
name="get_weather",
|
|
arguments='{"location": "NYC"}',
|
|
)
|
|
assert should_continue_final_message([tool_call]) is False
|
|
|
|
tool_call = {
|
|
"id": "msg_123",
|
|
"call_id": "call_123",
|
|
"type": "function_call",
|
|
"status": "in_progress",
|
|
"name": "get_weather",
|
|
"arguments": '{"location": "NYC"}',
|
|
}
|
|
assert should_continue_final_message([tool_call]) is False
|
|
|
|
# Tests for dict inputs (e.g., from curl requests)
|
|
def test_dict_in_progress_message_returns_true(self):
|
|
"""Dict with in_progress status should be continued (curl input)."""
|
|
dict_item = {
|
|
"id": "msg_123",
|
|
"type": "message",
|
|
"role": "assistant",
|
|
"status": "in_progress",
|
|
"content": [{"type": "output_text", "text": "The answer is ("}],
|
|
}
|
|
assert should_continue_final_message([dict_item]) is True
|
|
|
|
def test_dict_incomplete_message_returns_true(self):
|
|
"""Dict with incomplete status should be continued (curl input)."""
|
|
dict_item = {
|
|
"id": "msg_123",
|
|
"type": "message",
|
|
"role": "assistant",
|
|
"status": "incomplete",
|
|
"content": [{"type": "output_text", "text": "Partial answer"}],
|
|
}
|
|
assert should_continue_final_message([dict_item]) is True
|
|
|
|
def test_dict_completed_message_returns_false(self):
|
|
"""Dict with completed status should not be continued (curl input)."""
|
|
dict_item = {
|
|
"id": "msg_123",
|
|
"type": "message",
|
|
"role": "assistant",
|
|
"status": "completed",
|
|
"content": [{"type": "output_text", "text": "Complete answer."}],
|
|
}
|
|
assert should_continue_final_message([dict_item]) is False
|
|
|
|
def test_dict_reasoning_in_progress_returns_true(self):
|
|
"""Dict reasoning item with in_progress status should be continued."""
|
|
dict_item = {
|
|
"id": "reasoning_123",
|
|
"type": "reasoning",
|
|
"status": "in_progress",
|
|
"content": [{"type": "reasoning_text", "text": "Let me think..."}],
|
|
}
|
|
assert should_continue_final_message([dict_item]) is True
|
|
|
|
def test_dict_without_status_returns_false(self):
|
|
"""Dict without status field should not be continued."""
|
|
dict_item = {
|
|
"id": "msg_123",
|
|
"type": "message",
|
|
"role": "assistant",
|
|
"content": [{"type": "output_text", "text": "Some text"}],
|
|
}
|
|
assert should_continue_final_message([dict_item]) is False
|
|
|
|
def test_dict_with_none_status_returns_false(self):
|
|
"""Dict with None status should not be continued."""
|
|
dict_item = {
|
|
"id": "msg_123",
|
|
"type": "message",
|
|
"role": "assistant",
|
|
"status": None,
|
|
"content": [{"type": "output_text", "text": "Some text"}],
|
|
}
|
|
assert should_continue_final_message([dict_item]) is False
|
|
|
|
|
|
class TestMaybeCombineReasoningAndToolCall:
|
|
"""Tests for _maybe_combine_reasoning_and_tool_call function."""
|
|
|
|
def test_returns_none_when_item_id_is_none(self):
|
|
"""
|
|
Test fix from PR #31999: when item.id is None, should return None
|
|
instead of raising TypeError on startswith().
|
|
"""
|
|
item = ResponseFunctionToolCall(
|
|
type="function_call",
|
|
id=None, # This was causing TypeError before the fix
|
|
call_id="call_123",
|
|
name="test_function",
|
|
arguments="{}",
|
|
)
|
|
messages: list[ChatCompletionMessageParam] = []
|
|
|
|
result = _maybe_combine_reasoning_and_tool_call(item, messages)
|
|
|
|
assert result is None
|
|
|
|
def test_returns_none_when_id_does_not_start_with_mcp_prefix(self):
|
|
"""Test that non-MCP tool calls are not combined."""
|
|
item = ResponseFunctionToolCall(
|
|
type="function_call",
|
|
id="regular_id", # Does not start with MCP_PREFIX
|
|
call_id="call_123",
|
|
name="test_function",
|
|
arguments="{}",
|
|
)
|
|
messages = [{"role": "assistant", "reasoning": "some reasoning"}]
|
|
|
|
result = _maybe_combine_reasoning_and_tool_call(item, messages)
|
|
|
|
assert result is None
|
|
|
|
def test_returns_none_when_last_message_is_not_assistant(self):
|
|
"""Test that non-assistant last message returns None."""
|
|
item = ResponseFunctionToolCall(
|
|
type="function_call",
|
|
id=f"{MCP_PREFIX}tool_id",
|
|
call_id="call_123",
|
|
name="test_function",
|
|
arguments="{}",
|
|
)
|
|
messages = [{"role": "user", "content": "hello"}]
|
|
|
|
result = _maybe_combine_reasoning_and_tool_call(item, messages)
|
|
|
|
assert result is None
|
|
|
|
def test_returns_none_when_last_message_has_no_reasoning(self):
|
|
"""Test that assistant message without reasoning returns None."""
|
|
item = ResponseFunctionToolCall(
|
|
type="function_call",
|
|
id=f"{MCP_PREFIX}tool_id",
|
|
call_id="call_123",
|
|
name="test_function",
|
|
arguments="{}",
|
|
)
|
|
messages = [{"role": "assistant", "content": "some content"}]
|
|
|
|
result = _maybe_combine_reasoning_and_tool_call(item, messages)
|
|
|
|
assert result is None
|
|
|
|
def test_combines_reasoning_and_mcp_tool_call(self):
|
|
"""Test successful combination of reasoning message and MCP tool call."""
|
|
item = ResponseFunctionToolCall(
|
|
type="function_call",
|
|
id=f"{MCP_PREFIX}tool_id",
|
|
call_id="call_123",
|
|
name="test_function",
|
|
arguments='{"arg": "value"}',
|
|
)
|
|
messages = [{"role": "assistant", "reasoning": "I need to call this tool"}]
|
|
|
|
result = _maybe_combine_reasoning_and_tool_call(item, messages)
|
|
|
|
assert result is not None
|
|
assert result["role"] == "assistant"
|
|
assert result["reasoning"] == "I need to call this tool"
|
|
assert "tool_calls" in result
|
|
assert len(result["tool_calls"]) == 1
|
|
assert result["tool_calls"][0]["id"] == "call_123"
|
|
assert result["tool_calls"][0]["function"]["name"] == "test_function"
|
|
assert result["tool_calls"][0]["function"]["arguments"] == '{"arg": "value"}'
|
|
assert result["tool_calls"][0]["type"] == "function"
|
|
|
|
def test_returns_none_for_non_function_tool_call_type(self):
|
|
"""Test that non-ResponseFunctionToolCall items return None."""
|
|
# Pass a dict instead of ResponseFunctionToolCall
|
|
item = {"type": "message", "content": "hello"}
|
|
messages = [{"role": "assistant", "reasoning": "some reasoning"}]
|
|
|
|
result = _maybe_combine_reasoning_and_tool_call(item, messages)
|
|
|
|
assert result is None
|
|
|
|
def test_returns_none_when_id_is_empty_string(self):
|
|
"""Test that empty string id returns None (falsy check)."""
|
|
item = ResponseFunctionToolCall(
|
|
type="function_call",
|
|
id="", # Empty string is falsy
|
|
call_id="call_123",
|
|
name="test_function",
|
|
arguments="{}",
|
|
)
|
|
messages = [{"role": "assistant", "reasoning": "some reasoning"}]
|
|
|
|
result = _maybe_combine_reasoning_and_tool_call(item, messages)
|
|
|
|
assert result is None
|