vllm/tests/entrypoints/openai/test_completion_with_functi...

156 lines
4.9 KiB
Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import openai # use the official client for correctness check
import pytest
import pytest_asyncio
# downloading lora to test lora requests
from ...utils import RemoteOpenAIServer
# any model with a chat template should work here
MODEL_NAME = "Qwen/Qwen3-0.6B"
@pytest.fixture(scope="module")
def server(): # noqa: F811
args = [
# use half precision for speed and memory savings in CI environment
"--dtype",
"half",
"--enable-auto-tool-choice",
"--guided-decoding-backend",
"xgrammar",
"--tool-call-parser",
"hermes"
]
with RemoteOpenAIServer(MODEL_NAME, args) as remote_server:
yield remote_server
@pytest_asyncio.fixture
async def client(server):
async with server.get_async_client() as async_client:
yield async_client
@pytest.mark.asyncio
@pytest.mark.parametrize("model_name", [MODEL_NAME])
async def test_required_tool_use(client: openai.AsyncOpenAI, model_name: str):
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. 'Vienna'",
"default": "Vienna",
},
"country": {
"type":
"string",
"description":
"The country that the city is in, e.g. 'Austria'",
},
"unit": {
"type": "string",
"description":
"The unit to fetch the temperature in",
"enum": ["celsius", "fahrenheit"],
},
},
"required": ["country", "unit"],
},
},
},
{
"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. 'Vienna'",
"default": "Vienna",
},
"country": {
"type":
"string",
"description":
"The country that the city is in, e.g. 'Austria'",
},
"days": {
"type":
"integer",
"description":
"Number of days to get the forecast for (1-7)",
},
"unit": {
"type": "string",
"description":
"The unit to fetch the temperature in",
"enum": ["celsius", "fahrenheit"],
},
},
"required": ["country", "days", "unit"],
},
},
},
]
messages = [
{
"role": "user",
"content": "Hi! How are you doing today?"
},
{
"role": "assistant",
"content": "I'm doing well! How can I help you?"
},
{
"role":
"user",
"content":
"Can you tell me what the current weather is in Berlin and the "\
"forecast for the next 5 days, in fahrenheit?",
},
]
# Non-streaming test
chat_completion = await client.chat.completions.create(
messages=messages,
model=model_name,
tools=tools,
tool_choice="required",
)
assert chat_completion.choices[0].message.tool_calls is not None
assert len(chat_completion.choices[0].message.tool_calls) > 0
# Streaming test
stream = await client.chat.completions.create(
messages=messages,
model=model_name,
tools=tools,
tool_choice="required",
stream=True,
)
output = []
async for chunk in stream:
if chunk.choices and chunk.choices[0].delta.tool_calls:
output.extend(chunk.choices[0].delta.tool_calls)
assert len(output) > 0