[Test] Consolidate tool parser unit tests to tests/tool_parsers (#37834)
Signed-off-by: Ben Browning <bbrownin@redhat.com>
This commit is contained in:
Ben Browning
179
tests/tool_parsers/test_hunyuan_a13b_tool_parser.py
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179
tests/tool_parsers/test_hunyuan_a13b_tool_parser.py
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# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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# ruff: noqa: E501
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import json
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from unittest.mock import MagicMock
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import pytest
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from tests.tool_parsers.utils import (
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run_tool_extraction,
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run_tool_extraction_streaming,
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)
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from vllm.entrypoints.openai.engine.protocol import FunctionCall, ToolCall
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from vllm.tool_parsers import ToolParser, ToolParserManager
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def make_tool_call(name, arguments):
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return ToolCall(
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type="function",
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function=FunctionCall(name=name, arguments=json.dumps(arguments)),
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)
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# TODO: add reason prefix and suffix.
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@pytest.mark.parametrize(
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"model_output,expected_tool_calls,expected_content",
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[
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# No tool call
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("How can I help you today?", [], "How can I help you today?"),
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# Single tool call, no content
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(
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'<tool_calls>[{"name": "get_weather", "arguments": {"city": "San Francisco", "metric": "celsius"}}]</tool_calls>', # noqa: E501
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[
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make_tool_call(
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"get_weather", {"city": "San Francisco", "metric": "celsius"}
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)
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],
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None,
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),
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# Multiple tool calls
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(
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'<tool_calls>[{"name": "get_weather", "arguments": {"city": "San Francisco", "metric": "celsius"}}, {"name": "register_user", "arguments": {"name": "John Doe", "age": 37, "address": {"city": "San Francisco", "state": "CA"}, "role": null, "passed_test": true, "aliases": ["John", "Johnny"]}}]</tool_calls>', # noqa: E501
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[
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make_tool_call(
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"get_weather", {"city": "San Francisco", "metric": "celsius"}
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),
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make_tool_call(
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"register_user",
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{
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"name": "John Doe",
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"age": 37,
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"address": {"city": "San Francisco", "state": "CA"},
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"role": None,
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"passed_test": True,
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"aliases": ["John", "Johnny"],
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},
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),
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],
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None,
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),
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# Content before tool call
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(
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'I will call the tool now. <tool_calls>[{"name": "get_weather", "arguments": {"city": "Boston"}}]</tool_calls>', # noqa: E501
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[make_tool_call("get_weather", {"city": "Boston"})],
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"I will call the tool now. ",
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),
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# Content after tool call (should be stripped)
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(
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'<tool_calls>[{"name": "get_weather", "arguments": {"city": "Seattle"}}]</tool_calls>\nThank you!', # noqa: E501
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[make_tool_call("get_weather", {"city": "Seattle"})],
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None,
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),
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(
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'<tool_calls>[{"name": "complex_tool", "arguments": {"level1": {"level2": {"level3": {"value": 123}}}}}]</tool_calls>',
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[
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make_tool_call(
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"complex_tool", {"level1": {"level2": {"level3": {"value": 123}}}}
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)
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],
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None,
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),
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],
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)
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def test_hunyuan_a13b_tool_parser_extract(
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model_output, expected_tool_calls, expected_content
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):
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mock_tokenizer = MagicMock()
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tool_parser: ToolParser = ToolParserManager.get_tool_parser("hunyuan_a13b")(
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mock_tokenizer
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)
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content, tool_calls = run_tool_extraction(
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tool_parser, model_output, streaming=False
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)
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# align the random id.
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for idx in range(len(tool_calls)):
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tool_calls[idx].id = expected_tool_calls[idx].id
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assert tool_calls == expected_tool_calls
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assert content == expected_content
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# Streaming test: simulate incremental output
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@pytest.mark.parametrize(
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"model_deltas,expected_tool_calls",
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[
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(
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[
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'<tool_calls>[{"name": "get_weather", ',
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'"arguments": {"city": "San Francisco", ',
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'"metric": "celsius"}}]',
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"</tool_calls>",
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],
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[
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make_tool_call(
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"get_weather", {"city": "San Francisco", "metric": "celsius"}
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)
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],
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),
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(
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[
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'<tool_calls>[{"name":',
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' "get_weather",',
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' "arguments":',
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' {"city": "Boston"}',
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"}]",
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"</tool_calls>",
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],
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[make_tool_call("get_weather", {"city": "Boston"})],
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),
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(
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[
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"",
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'<tool_calls>[{"name":',
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' "get_weather",',
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' "arguments":',
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' {"city": "Boston"}',
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"}]",
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"</tool_calls>",
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"\n</answer>",
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],
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[make_tool_call("get_weather", {"city": "Boston"})],
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),
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pytest.param(
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[
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'<tool_calls>[{"name": "complex_tool",',
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' "arguments": ',
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' {"level1": {"level2": ',
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'{"level3": {"value": 123}}}}}',
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"]</tool_calls>",
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],
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[
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make_tool_call(
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"complex_tool", {"level1": {"level2": {"level3": {"value": 123}}}}
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)
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],
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marks=pytest.mark.xfail(
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reason="stream parsing not support nested json yet."
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),
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),
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],
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)
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def test_hunyuan_a13b_tool_parser_streaming(model_deltas, expected_tool_calls):
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mock_tokenizer = MagicMock()
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tool_parser: ToolParser = ToolParserManager.get_tool_parser("hunyuan_a13b")(
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mock_tokenizer
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)
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reconstructor = run_tool_extraction_streaming(
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tool_parser, model_deltas, assert_one_tool_per_delta=False
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)
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# align the random id.
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for idx in range(len(reconstructor.tool_calls)):
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reconstructor.tool_calls[idx].id = expected_tool_calls[idx].id
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assert reconstructor.tool_calls == expected_tool_calls
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