vllm/tests/tool_use/test_openai_tool_parser.py
Aaron Pham c29fb540ff
[gpt-oss] tool parser supports for /chat/completions [1/n] (#22386)
Signed-off-by: Aaron Pham <contact@aarnphm.xyz>
Co-authored-by: Simon Mo <simon.mo@hey.com>
2025-09-04 20:39:12 -07:00

148 lines
5.3 KiB
Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import json
import pytest
from openai_harmony import (Conversation, DeveloperContent,
HarmonyEncodingName, Message, Role, SystemContent,
load_harmony_encoding)
from vllm.entrypoints.openai.protocol import FunctionCall, ToolCall
from vllm.entrypoints.openai.tool_parsers import OpenAIToolParser
from vllm.transformers_utils.tokenizer import get_tokenizer
MODEL = "gpt2"
@pytest.fixture(scope="module")
def openai_tokenizer():
# The parser does not use the tokenizer, but the constructor requires it.
return get_tokenizer(MODEL)
@pytest.fixture
def openai_tool_parser(openai_tokenizer):
return OpenAIToolParser(openai_tokenizer)
@pytest.fixture(scope="module")
def harmony_encoding():
return load_harmony_encoding(HarmonyEncodingName.HARMONY_GPT_OSS)
def assert_tool_calls(
actual_tool_calls: list[ToolCall],
expected_tool_calls: list[ToolCall],
):
assert len(actual_tool_calls) == len(expected_tool_calls)
for actual_tool_call, expected_tool_call in zip(actual_tool_calls,
expected_tool_calls):
assert isinstance(actual_tool_call.id, str)
assert len(actual_tool_call.id) > 16 # Default from protocol.py
assert actual_tool_call.type == "function"
assert actual_tool_call.function == expected_tool_call.function
def test_extract_tool_calls_no_tools(openai_tool_parser, harmony_encoding):
convo = Conversation.from_messages([
Message.from_role_and_content(
Role.SYSTEM,
SystemContent.new(),
),
Message.from_role_and_content(
Role.DEVELOPER,
DeveloperContent.new().with_instructions("Talk like a pirate!")),
Message.from_role_and_content(Role.USER, "Arrr, how be you?"),
Message.from_role_and_content(Role.ASSISTANT,
"This is a test").with_channel("final")
])
token_ids = harmony_encoding.render_conversation_for_completion(
convo, Role.ASSISTANT)
extracted_info = openai_tool_parser.extract_tool_calls(
"",
request=None,
token_ids=token_ids,
)
assert not extracted_info.tools_called
assert extracted_info.tool_calls == []
assert extracted_info.content == "This is a test"
def test_extract_tool_calls_single_tool(openai_tool_parser, harmony_encoding):
convo = Conversation.from_messages([
Message.from_role_and_content(Role.USER,
"What is the weather in Tokyo?"),
Message.from_role_and_content(
Role.ASSISTANT,
'User asks: "What is the weather in Tokyo?" We need to use get_current_weather tool.', # noqa: E501
).with_channel("analysis"),
Message.from_role_and_content(
Role.ASSISTANT,
'{"location": "Tokyo"}').with_channel("commentary").with_recipient(
"functions.get_current_weather").with_content_type("json"),
])
token_ids = harmony_encoding.render_conversation_for_completion(
convo, Role.ASSISTANT)
extracted_info = openai_tool_parser.extract_tool_calls(
"",
request=None,
token_ids=token_ids,
)
assert extracted_info.tools_called
expected_tool_calls = [
ToolCall(function=FunctionCall(
name="get_current_weather",
arguments=json.dumps({"location": "Tokyo"}),
))
]
assert_tool_calls(extracted_info.tool_calls, expected_tool_calls)
assert extracted_info.content is None
def test_extract_tool_calls_multiple_tools(
openai_tool_parser,
harmony_encoding,
):
convo = Conversation.from_messages([
Message.from_role_and_content(
Role.USER, "What is the weather in Tokyo based on where I'm at?"),
Message.from_role_and_content(
Role.ASSISTANT,
'User asks: "What is the weather in Tokyo?" based on their location. We need to use get_current_weather tool and get_user_location tool.', # noqa: E501
).with_channel("analysis"),
Message.from_role_and_content(
Role.ASSISTANT,
'{"location": "Tokyo"}').with_channel("commentary").with_recipient(
"functions.get_current_weather").with_content_type("json"),
Message.from_role_and_content(
Role.ASSISTANT,
'{"location": "Tokyo"}').with_channel("commentary").with_recipient(
"functions.get_user_location").with_content_type("json"),
])
token_ids = harmony_encoding.render_conversation_for_completion(
convo,
Role.ASSISTANT,
)
extracted_info = openai_tool_parser.extract_tool_calls(
"",
request=None,
token_ids=token_ids,
)
assert extracted_info.tools_called
expected_tool_calls = [
ToolCall(function=FunctionCall(
name="get_current_weather",
arguments=json.dumps({"location": "Tokyo"}),
)),
ToolCall(function=FunctionCall(
name="get_user_location",
arguments=json.dumps({"location": "Tokyo"}),
))
]
assert_tool_calls(extracted_info.tool_calls, expected_tool_calls)
assert extracted_info.content is None