vllm/tests/tool_use/test_xlam_tool_parser.py

247 lines
9.0 KiB
Python

# SPDX-License-Identifier: Apache-2.0
import json
import pytest
from vllm.entrypoints.openai.protocol import FunctionCall, ToolCall
from vllm.entrypoints.openai.tool_parsers import xLAMToolParser
from vllm.transformers_utils.tokenizer import get_tokenizer
# Use a common model that is likely to be available
MODEL = "Salesforce/Llama-xLAM-2-8B-fc-r"
@pytest.fixture(scope="module")
def xlam_tokenizer():
return get_tokenizer(tokenizer_name=MODEL)
@pytest.fixture
def xlam_tool_parser(xlam_tokenizer):
return xLAMToolParser(xlam_tokenizer)
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
assert actual_tool_call.type == "function"
assert actual_tool_call.function == expected_tool_call.function
def test_extract_tool_calls_no_tools(xlam_tool_parser):
model_output = "This is a test"
extracted_tool_calls = xlam_tool_parser.extract_tool_calls(
model_output, request=None) # type: ignore[arg-type]
assert not extracted_tool_calls.tools_called
assert extracted_tool_calls.tool_calls == []
assert extracted_tool_calls.content == model_output
@pytest.mark.parametrize(
ids=[
"parallel_tool_calls",
"single_tool_with_think_tag",
"single_tool_with_json_code_block",
"single_tool_with_tool_calls_tag",
],
argnames=["model_output", "expected_tool_calls", "expected_content"],
argvalues=[
(
"""[{"name": "get_current_weather", "arguments": {"city": "Dallas", "state": "TX", "unit": "fahrenheit"}}, {"name": "get_current_weather", "arguments": {"city": "Orlando", "state": "FL", "unit": "fahrenheit"}}]""", # noqa: E501
[
ToolCall(function=FunctionCall(
name="get_current_weather",
arguments=json.dumps({
"city": "Dallas",
"state": "TX",
"unit": "fahrenheit",
}),
)),
ToolCall(function=FunctionCall(
name="get_current_weather",
arguments=json.dumps({
"city": "Orlando",
"state": "FL",
"unit": "fahrenheit",
}),
)),
],
None,
),
(
"""<think>I'll help you with that.</think>[{"name": "get_current_weather", "arguments": {"city": "Dallas", "state": "TX", "unit": "fahrenheit"}}]""", # noqa: E501
[
ToolCall(function=FunctionCall(
name="get_current_weather",
arguments=json.dumps({
"city": "Dallas",
"state": "TX",
"unit": "fahrenheit",
}),
))
],
"<think>I'll help you with that.</think>",
),
(
"""I'll help you with that.\n```json\n[{"name": "get_current_weather", "arguments": {"city": "Dallas", "state": "TX", "unit": "fahrenheit"}}]\n```""", # noqa: E501
[
ToolCall(function=FunctionCall(
name="get_current_weather",
arguments=json.dumps({
"city": "Dallas",
"state": "TX",
"unit": "fahrenheit",
}),
))
],
"I'll help you with that.",
),
(
"""I'll check the weather for you.[TOOL_CALLS][{"name": "get_current_weather", "arguments": {"city": "Dallas", "state": "TX", "unit": "fahrenheit"}}]""", # noqa: E501
[
ToolCall(function=FunctionCall(
name="get_current_weather",
arguments=json.dumps({
"city": "Dallas",
"state": "TX",
"unit": "fahrenheit",
}),
))
],
"I'll check the weather for you.",
),
],
)
def test_extract_tool_calls(xlam_tool_parser, model_output,
expected_tool_calls, expected_content):
extracted_tool_calls = xlam_tool_parser.extract_tool_calls(
model_output, request=None) # type: ignore[arg-type]
assert extracted_tool_calls.tools_called
assert_tool_calls(extracted_tool_calls.tool_calls, expected_tool_calls)
assert extracted_tool_calls.content == expected_content
@pytest.mark.parametrize(
ids=["list_structured_tool_call"],
argnames=["model_output", "expected_tool_calls", "expected_content"],
argvalues=[
(
"""[{"name": "get_current_weather", "arguments": {"city": "Seattle", "state": "WA", "unit": "celsius"}}]""", # noqa: E501
[
ToolCall(function=FunctionCall(
name="get_current_weather",
arguments=json.dumps({
"city": "Seattle",
"state": "WA",
"unit": "celsius",
}),
))
],
None,
),
],
)
def test_extract_tool_calls_list_structure(xlam_tool_parser, model_output,
expected_tool_calls,
expected_content):
"""Test extraction of tool calls when the model outputs a list-structured tool call.""" # noqa: E501
extracted_tool_calls = xlam_tool_parser.extract_tool_calls(
model_output, request=None) # type: ignore[arg-type]
assert extracted_tool_calls.tools_called
assert_tool_calls(extracted_tool_calls.tool_calls, expected_tool_calls)
assert extracted_tool_calls.content == expected_content
# Test for preprocess_model_output method
def test_preprocess_model_output(xlam_tool_parser):
# Test with list structure
model_output = """[{"name": "get_current_weather", "arguments": {"city": "Seattle"}}]""" # noqa: E501
content, potential_tool_calls = xlam_tool_parser.preprocess_model_output(
model_output)
assert content is None
assert potential_tool_calls == model_output
# Test with thinking tag
model_output = """<think>I'll help you with that.</think>[{"name": "get_current_weather", "arguments": {"city": "Seattle"}}]""" # noqa: E501
content, potential_tool_calls = xlam_tool_parser.preprocess_model_output(
model_output)
assert content == "<think>I'll help you with that.</think>"
assert (
potential_tool_calls ==
'[{"name": "get_current_weather", "arguments": {"city": "Seattle"}}]')
# Test with JSON code block
model_output = """I'll help you with that.
```json
[{"name": "get_current_weather", "arguments": {"city": "Seattle"}}]
```"""
content, potential_tool_calls = xlam_tool_parser.preprocess_model_output(
model_output)
assert content == "I'll help you with that."
assert "get_current_weather" in potential_tool_calls
# Test with no tool calls
model_output = """I'll help you with that."""
content, potential_tool_calls = xlam_tool_parser.preprocess_model_output(
model_output)
assert content == model_output
assert potential_tool_calls is None
# Simulate streaming to test extract_tool_calls_streaming
def test_streaming_with_list_structure(xlam_tool_parser):
# Reset streaming state
xlam_tool_parser.prev_tool_calls = []
xlam_tool_parser.current_tools_sent = []
xlam_tool_parser.streamed_args = []
xlam_tool_parser.current_tool_id = -1
# Simulate receiving a message with list structure
current_text = """[{"name": "get_current_weather", "arguments": {"city": "Seattle"}}]""" # noqa: E501
# First call to set up the tool
xlam_tool_parser.extract_tool_calls_streaming(
previous_text="",
current_text=current_text,
delta_text="]",
previous_token_ids=[],
current_token_ids=[],
delta_token_ids=[],
request=None,
)
# Make sure the tool is set up correctly
assert (xlam_tool_parser.current_tool_id
>= 0), "Tool index should be initialized"
# Manually set up the state for sending the tool name
xlam_tool_parser.current_tools_sent = [False]
# Call to send the function name
result = xlam_tool_parser.extract_tool_calls_streaming(
previous_text=current_text,
current_text=current_text,
delta_text="",
previous_token_ids=[],
current_token_ids=[],
delta_token_ids=[],
request=None,
)
# Check that we get a result with the proper tool call
if result is not None:
assert hasattr(result, "tool_calls")
assert len(result.tool_calls) == 1
assert result.tool_calls[0].function.name == "get_current_weather"