vllm/tests/async_engine/test_openapi_server_ray.py

158 lines
5.1 KiB
Python

# imports for guided decoding tests
import os
import subprocess
import sys
import time
import openai # use the official client for correctness check
import pytest
# using Ray for overall ease of process management, parallel requests,
# and debugging.
import ray
import requests
MAX_SERVER_START_WAIT_S = 600 # wait for server to start for 60 seconds
# any model with a chat template should work here
MODEL_NAME = "facebook/opt-125m"
@ray.remote(num_gpus=1)
class ServerRunner:
def __init__(self, args):
env = os.environ.copy()
env["PYTHONUNBUFFERED"] = "1"
self.proc = subprocess.Popen(
["python3", "-m", "vllm.entrypoints.openai.api_server"] + args,
env=env,
stdout=sys.stdout,
stderr=sys.stderr,
)
self._wait_for_server()
def ready(self):
return True
def _wait_for_server(self):
# run health check
start = time.time()
while True:
try:
if requests.get(
"http://localhost:8000/health").status_code == 200:
break
except Exception as err:
if self.proc.poll() is not None:
raise RuntimeError("Server exited unexpectedly.") from err
time.sleep(0.5)
if time.time() - start > MAX_SERVER_START_WAIT_S:
raise RuntimeError(
"Server failed to start in time.") from err
def __del__(self):
if hasattr(self, "proc"):
self.proc.terminate()
@pytest.fixture(scope="session")
def server():
ray.init()
server_runner = ServerRunner.remote([
"--model",
MODEL_NAME,
# use half precision for speed and memory savings in CI environment
"--dtype",
"float16",
"--max-model-len",
"2048",
"--enforce-eager",
"--engine-use-ray"
])
ray.get(server_runner.ready.remote())
yield server_runner
ray.shutdown()
@pytest.fixture(scope="session")
def client():
client = openai.AsyncOpenAI(
base_url="http://localhost:8000/v1",
api_key="token-abc123",
)
yield client
@pytest.mark.asyncio
async def test_check_models(server, client: openai.AsyncOpenAI):
models = await client.models.list()
models = models.data
served_model = models[0]
assert served_model.id == MODEL_NAME
assert all(model.root == MODEL_NAME for model in models)
@pytest.mark.asyncio
async def test_single_completion(server, client: openai.AsyncOpenAI):
completion = await client.completions.create(model=MODEL_NAME,
prompt="Hello, my name is",
max_tokens=5,
temperature=0.0)
assert completion.id is not None
assert completion.choices is not None and len(completion.choices) == 1
assert completion.choices[0].text is not None and len(
completion.choices[0].text) >= 5
assert completion.choices[0].finish_reason == "length"
assert completion.usage == openai.types.CompletionUsage(
completion_tokens=5, prompt_tokens=6, total_tokens=11)
# test using token IDs
completion = await client.completions.create(
model=MODEL_NAME,
prompt=[0, 0, 0, 0, 0],
max_tokens=5,
temperature=0.0,
)
assert completion.choices[0].text is not None and len(
completion.choices[0].text) >= 5
@pytest.mark.asyncio
async def test_single_chat_session(server, client: openai.AsyncOpenAI):
messages = [{
"role": "system",
"content": "you are a helpful assistant"
}, {
"role": "user",
"content": "what is 1+1?"
}]
# test single completion
chat_completion = await client.chat.completions.create(model=MODEL_NAME,
messages=messages,
max_tokens=10,
logprobs=True,
top_logprobs=5)
assert chat_completion.id is not None
assert chat_completion.choices is not None and len(
chat_completion.choices) == 1
assert chat_completion.choices[0].message is not None
assert chat_completion.choices[0].logprobs is not None
assert chat_completion.choices[0].logprobs.top_logprobs is not None
assert len(chat_completion.choices[0].logprobs.top_logprobs[0]) == 5
message = chat_completion.choices[0].message
assert message.content is not None and len(message.content) >= 10
assert message.role == "assistant"
messages.append({"role": "assistant", "content": message.content})
# test multi-turn dialogue
messages.append({"role": "user", "content": "express your result in json"})
chat_completion = await client.chat.completions.create(
model=MODEL_NAME,
messages=messages,
max_tokens=10,
)
message = chat_completion.choices[0].message
assert message.content is not None and len(message.content) >= 0