Files
sglang/test/srt/test_large_max_new_tokens.py

77 lines
2.3 KiB
Python

import json
import os
import time
import unittest
from concurrent.futures import ThreadPoolExecutor
import openai
from sglang.srt.hf_transformers_utils import get_tokenizer
from sglang.srt.utils import kill_child_process
from sglang.test.test_utils import (
DEFAULT_MODEL_NAME_FOR_TEST,
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
DEFAULT_URL_FOR_TEST,
popen_launch_server,
)
class TestOpenAIServer(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.model = DEFAULT_MODEL_NAME_FOR_TEST
cls.base_url = DEFAULT_URL_FOR_TEST
cls.api_key = "sk-123456"
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
api_key=cls.api_key,
other_args=("--max-total-token", "1024", "--context-len", "8192"),
env={"SGLANG_CLIP_MAX_NEW_TOKENS": "256", **os.environ},
return_stdout_stderr=True,
)
cls.base_url += "/v1"
cls.tokenizer = get_tokenizer(DEFAULT_MODEL_NAME_FOR_TEST)
@classmethod
def tearDownClass(cls):
kill_child_process(cls.process.pid)
def run_chat_completion(self):
client = openai.Client(api_key=self.api_key, base_url=self.base_url)
response = client.chat.completions.create(
model=self.model,
messages=[
{"role": "system", "content": "You are a helpful AI assistant"},
{
"role": "user",
"content": "Please repeat the world 'hello' for 10000 times.",
},
],
temperature=0,
)
return response
def test_chat_completion(self):
num_requests = 4
futures = []
with ThreadPoolExecutor(16) as executor:
for i in range(num_requests):
futures.append(executor.submit(self.run_chat_completion))
all_requests_running = False
for line in iter(self.process.stderr.readline, ""):
line = str(line)
print(line, end="")
if f"#running-req: {num_requests}" in line:
all_requests_running = True
break
assert all_requests_running
if __name__ == "__main__":
unittest.main()