Files
vllm/tests/tool_use/test_tool_choice_required.py
2025-10-06 05:12:40 +00:00

330 lines
10 KiB
Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import json
from copy import deepcopy
from unittest.mock import MagicMock
import pytest
import regex as re
from pydantic import TypeAdapter
from vllm.entrypoints.openai.protocol import (
ChatCompletionRequest,
ChatCompletionToolsParam,
)
from vllm.entrypoints.openai.serving_chat import OpenAIServingChat
pytestmark = pytest.mark.cpu_test
EXAMPLE_TOOLS = [
{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"city": {
"type": "string",
"description": "The city to find the weather for"
", e.g. 'San Francisco'",
},
},
"required": ["city"],
"additionalProperties": False,
},
},
"strict": True,
},
{
"type": "function",
"function": {
"name": "get_forecast",
"description": "Get the weather forecast for a given location",
"parameters": {
"type": "object",
"properties": {
"city": {
"type": "string",
"description": "The city to get the forecast for, e.g. "
"'New York'",
},
"days": {
"type": "integer",
"description": "Number of days to get the forecast for (1-7)",
},
},
"required": ["city", "days"],
"additionalProperties": False,
},
},
"strict": True,
},
]
def _compile_and_check(
tools: list[ChatCompletionToolsParam], sample_output, should_match: bool
):
self = MagicMock(tool_choice="required", tools=tools)
schema = ChatCompletionRequest._get_json_schema_from_tool(self)
assert isinstance(schema, dict)
# use build_regex_from_schema used in JSONLogitsProcessor to create Guide
from outlines_core.json_schema import build_regex_from_schema
regex = build_regex_from_schema(json.dumps(schema))
compiled = re.compile(regex)
matches = compiled.fullmatch(json.dumps(sample_output)) is not None
assert matches == should_match
VALID_TOOL_OUTPUTS = [
([{"name": "get_current_weather", "parameters": {"city": "Vienna"}}], True),
(
[
{"name": "get_current_weather", "parameters": {"city": "Vienna"}},
{"name": "get_current_weather", "parameters": {"city": "Berlin"}},
],
True,
),
([{"name": "get_forecast", "parameters": {"city": "Vienna", "days": 7}}], True),
(
[
{"name": "get_forecast", "parameters": {"city": "Vienna", "days": 7}},
{"name": "get_current_weather", "parameters": {"city": "Vienna"}},
],
True,
),
(
[
{"name": "get_forecast", "parameters": {"city": "Vienna", "days": 7}},
{"name": "get_current_weather", "parameters": {"city": "Vienna"}},
{"name": "get_forecast", "parameters": {"city": "Berlin", "days": 7}},
{"name": "get_current_weather", "parameters": {"city": "Berlin"}},
],
True,
),
]
VALID_TOOLS = [t[0] for t in VALID_TOOL_OUTPUTS]
@pytest.mark.parametrize(
"sample_output, should_match",
VALID_TOOL_OUTPUTS
+ [
(None, False),
([], False), # empty list cannot be generated
({}, False), # empty object cannot be generated
([{}], False), # list with empty object cannot be generated
(
[
{ # function without required parameters cannot be generated
"name": "get_current_weather"
}
],
False,
),
(
[
{ # function without required parameters cannot be generated
"name": "get_current_weather",
"parameters": {},
}
],
False,
),
(
[
{ # function without required parameters cannot be generated
"name": "get_current_weather",
"parameters": None,
}
],
False,
),
(
{ # tool call without lists cannot be generated
"name": "get_current_weather",
"parameters": {"city": "Vienna"},
},
False,
),
(
[
{ # tool call with extra parameters cannot be generated
"name": "get_current_weather",
"parameters": {"city": "Vienna", "extra": "value"},
}
],
False,
),
(
[
{ # tool call where parameters are first cannot be generated
"parameters": {"city": "Vienna"},
"name": "get_current_weather",
}
],
False,
),
(
[
{ # tool call without all required parameters cannot be generated
"name": "get_forecast",
"parameters": {"city": "Vienna"},
}
],
False,
),
( # tool call with incorrect name/parameters cannot be generated
[{"name": "get_weather", "parameters": {"city": "Vienna", "days": 7}}],
False,
),
( # tool call with both valid and empty function cannot be generated
[{"name": "get_current_weather", "parameters": {"city": "Vienna"}}, {}],
False,
),
],
)
def test_structured_outputs_json(sample_output, should_match):
_compile_and_check(
tools=TypeAdapter(list[ChatCompletionToolsParam]).validate_python(
EXAMPLE_TOOLS
),
sample_output=sample_output,
should_match=should_match,
)
def update_parameters_none(tool: ChatCompletionToolsParam) -> ChatCompletionToolsParam:
tool.function.parameters = None
return tool
def update_parameters_empty_dict(
tool: ChatCompletionToolsParam,
) -> ChatCompletionToolsParam:
tool.function.parameters = {}
return tool
@pytest.mark.parametrize(
"sample_output, should_match",
[
(None, False),
([], False), # empty list cannot be generated
({}, False), # empty object cannot be generated
([{}], False), # list with empty object cannot be generated
(
[
{ # function without required parameters cannot be generated
"name": "get_current_weather"
}
],
False,
),
(
[
{ # function without required parameters cannot be generated
"name": "get_current_weather",
"parameters": None,
}
],
False,
),
(
[
{ # function with extra parameters cannot be generated
"name": "get_current_weather",
"parameters": {"extra": "value"},
}
],
False,
),
(
[
{ # only function with empty parameters object is valid
"name": "get_current_weather",
"parameters": {},
}
],
True,
),
],
)
@pytest.mark.parametrize(
"update_parameters", [update_parameters_none, update_parameters_empty_dict]
)
def test_structured_outputs_json_without_parameters(
sample_output, should_match, update_parameters
):
updated_tools = [deepcopy(EXAMPLE_TOOLS[0])]
tools = TypeAdapter(list[ChatCompletionToolsParam]).validate_python(updated_tools)
tools = list(map(update_parameters, tools))
assert all(
[
tool.function.parameters is None or tool.function.parameters == {}
for tool in tools
]
)
_compile_and_check(
tools=tools, sample_output=sample_output, should_match=should_match
)
@pytest.mark.parametrize("output", VALID_TOOLS)
@pytest.mark.parametrize("empty_params", [False, True])
@pytest.mark.parametrize("delta_len", [1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
def test_streaming_output_valid(output, empty_params, delta_len):
self = MagicMock()
output = deepcopy(output)
if empty_params:
output = [{"name": o["name"], "parameters": {}} for o in output]
output_json = json.dumps(output)
previous_text = ""
function_name_returned = False
messages = []
for i in range(0, len(output_json), delta_len):
delta_text = output_json[i : i + delta_len]
current_text = previous_text + delta_text
delta_message, function_name_returned = (
OpenAIServingChat.extract_tool_call_required_streaming(
self,
previous_text=previous_text,
current_text=current_text,
delta_text=delta_text,
function_name_returned=function_name_returned,
)
)
if delta_message:
messages.append(delta_message)
previous_text = current_text
assert len(messages) > 0
combined_messages = "["
for message in messages:
if message.tool_calls[0].function.name:
if len(combined_messages) > 1:
combined_messages += "},"
combined_messages += (
'{"name": "'
+ message.tool_calls[0].function.name
+ '", "parameters": '
+ message.tool_calls[0].function.arguments
)
else:
combined_messages += message.tool_calls[0].function.arguments
combined_messages += "}]"
assert json.loads(combined_messages) == output
assert json.dumps(json.loads(combined_messages)) == output_json