# SPDX-License-Identifier: Apache-2.0 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project import pytest import pytest_asyncio from openai import OpenAI from ...utils import RemoteOpenAIServer MODEL_NAME = "Qwen/Qwen3-8B" @pytest.fixture(scope="module") def server(): args = ["--reasoning-parser", "qwen3", "--max_model_len", "5000"] env_dict = dict( VLLM_ENABLE_RESPONSES_API_STORE="1", # uncomment for tool calling # PYTHON_EXECUTION_BACKEND="dangerously_use_uv", ) with RemoteOpenAIServer(MODEL_NAME, args, env_dict=env_dict) 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_basic(client: OpenAI, model_name: str): response = await client.responses.create( model=model_name, input="What is 13 * 24?", ) assert response is not None print("response: ", response) assert response.status == "completed" @pytest.mark.asyncio @pytest.mark.parametrize("model_name", [MODEL_NAME]) async def test_reasoning_item(client: OpenAI, model_name: str): response = await client.responses.create( model=model_name, input=[ {"type": "message", "content": "Hello.", "role": "user"}, { "type": "reasoning", "id": "lol", "content": [ { "type": "reasoning_text", "text": "We need to respond: greeting.", } ], "summary": [], }, ], temperature=0.0, ) assert response is not None assert response.status == "completed" # make sure we get a reasoning and text output assert response.output[0].type == "reasoning" assert response.output[1].type == "message" assert type(response.output[1].content[0].text) is str