vllm/tests/entrypoints/openai/test_async_tokenization.py
2024-11-27 13:21:10 -08:00

138 lines
3.7 KiB
Python

import asyncio
import contextlib
import random
import time
from typing import Callable
import openai
import pytest
import pytest_asyncio
import requests
from tests.utils import RemoteOpenAIServer
MODEL_NAME = "Qwen/Qwen2.5-1.5B-Instruct"
@pytest.fixture(scope="module")
def server(): # noqa: F811
args = [
# use half precision for speed and memory savings in CI environment
"--dtype",
"bfloat16",
"--max-model-len",
"8192",
"--enforce-eager",
"--max-num-seqs",
"128",
"--load-format",
"dummy",
]
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(
ids=["completion", "chat"],
argnames=["create_func_gen", "content_body"],
argvalues=[
(lambda x: x.completions.create, {
"prompt": " ".join(['A'] * 10_000)
}),
(lambda x: x.chat.completions.create, {
"messages": [{
"role": "user",
"content": " ".join(['A'] * 10_000)
}]
}),
],
)
async def test_with_and_without_truncate(
server: RemoteOpenAIServer,
client: openai.AsyncOpenAI,
create_func_gen: Callable,
content_body: dict,
):
create_func = create_func_gen(client)
body = {"model": MODEL_NAME, **content_body, "max_tokens": 10}
num_requests = 10
truncate_prompt_tokens = ([1000] * (num_requests // 2) + [None] *
(num_requests - num_requests // 2))
random.shuffle(truncate_prompt_tokens)
bodies = [{
**body, "extra_body": {
'truncate_prompt_tokens': t
}
} for t in truncate_prompt_tokens]
async def get_status_code(**kwargs):
try:
await create_func(**kwargs)
return 200
except openai.APIStatusError as e:
return e.status_code
responses = await asyncio.gather(*[get_status_code(**b) for b in bodies])
assert 500 not in responses
@pytest.mark.asyncio
@pytest.mark.parametrize(
ids=["single completion", "multiple completions", "chat"],
argnames=["create_func_gen", "content_body"],
argvalues=[
(lambda x: x.completions.create, {
"prompt": " ".join(['A'] * 300_000)
}),
(lambda x: x.completions.create, {
"prompt": [" ".join(['A'] * 300_000)] * 2
}),
(lambda x: x.chat.completions.create, {
"messages": [{
"role": "user",
"content": " ".join(['A'] * 300_000)
}]
}),
],
)
async def test_healthcheck_response_time(
server: RemoteOpenAIServer,
client: openai.AsyncOpenAI,
create_func_gen: Callable,
content_body: dict,
):
num_requests = 50
create_func = create_func_gen(client)
body = {"model": MODEL_NAME, **content_body, "max_tokens": 10}
def get_response_time(url):
start_time = time.monotonic()
res = requests.get(url)
end_time = time.monotonic()
assert res.status_code == 200
return end_time - start_time
no_load_response_time = get_response_time(server.url_for("health"))
tasks = [
asyncio.create_task(create_func(**body)) for _ in range(num_requests)
]
await asyncio.sleep(1) # give the tasks a chance to start running
load_response_time = get_response_time(server.url_for("health"))
with contextlib.suppress(openai.APIStatusError):
await asyncio.gather(*tasks)
assert load_response_time < 100 * no_load_response_time
assert load_response_time < 0.1