85 lines
2.5 KiB
Python
85 lines
2.5 KiB
Python
|
"""
|
||
|
|
python3 -m sglang.launch_server --model-path liuhaotian/llava-v1.5-7b --tokenizer-path llava-hf/llava-1.5-7b-hf --port 30000
|
||
|
|
|
||
|
|
Output:
|
||
|
|
The image features a man standing on the back of a yellow taxi cab, holding
|
||
|
|
"""
|
||
|
|
|
||
|
|
import argparse
|
||
|
|
import asyncio
|
||
|
|
import json
|
||
|
|
import time
|
||
|
|
|
||
|
|
import aiohttp
|
||
|
|
import requests
|
||
|
|
|
||
|
|
|
||
|
|
async def send_request(url, data, delay=0):
|
||
|
|
await asyncio.sleep(delay)
|
||
|
|
async with aiohttp.ClientSession() as session:
|
||
|
|
async with session.post(url, json=data) as resp:
|
||
|
|
output = await resp.json()
|
||
|
|
return output
|
||
|
|
|
||
|
|
|
||
|
|
async def test_concurrent(args):
|
||
|
|
url = f"{args.host}:{args.port}"
|
||
|
|
|
||
|
|
response = []
|
||
|
|
for i in range(8):
|
||
|
|
response.append(
|
||
|
|
send_request(
|
||
|
|
url + "/generate",
|
||
|
|
{
|
||
|
|
"text": "A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions. USER: <image>\nDescribe this picture ASSISTANT:",
|
||
|
|
"image_data": "/home/ubuntu/sglang/test/lang/image.png",
|
||
|
|
"sampling_params": {
|
||
|
|
"temperature": 0,
|
||
|
|
"max_new_tokens": 16,
|
||
|
|
},
|
||
|
|
},
|
||
|
|
)
|
||
|
|
)
|
||
|
|
|
||
|
|
rets = await asyncio.gather(*response)
|
||
|
|
for ret in rets:
|
||
|
|
print(ret["text"])
|
||
|
|
|
||
|
|
|
||
|
|
def test_streaming(args):
|
||
|
|
url = f"{args.host}:{args.port}"
|
||
|
|
|
||
|
|
response = requests.post(
|
||
|
|
url + "/generate",
|
||
|
|
json={
|
||
|
|
"text": "A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions. USER: <image>\nDescribe this picture ASSISTANT:",
|
||
|
|
"image_data": "/home/ubuntu/sglang/test/lang/image.png",
|
||
|
|
"sampling_params": {
|
||
|
|
"temperature": 0,
|
||
|
|
"max_new_tokens": 128,
|
||
|
|
},
|
||
|
|
"stream": True,
|
||
|
|
},
|
||
|
|
stream=True,
|
||
|
|
)
|
||
|
|
|
||
|
|
prev = 0
|
||
|
|
for chunk in response.iter_lines(decode_unicode=False, delimiter=b"\0"):
|
||
|
|
if chunk:
|
||
|
|
data = json.loads(chunk.decode())
|
||
|
|
output = data["text"].strip()
|
||
|
|
print(output[prev:], end="", flush=True)
|
||
|
|
prev = len(output)
|
||
|
|
print("")
|
||
|
|
|
||
|
|
|
||
|
|
if __name__ == "__main__":
|
||
|
|
parser = argparse.ArgumentParser()
|
||
|
|
parser.add_argument("--host", type=str, default="http://127.0.0.1")
|
||
|
|
parser.add_argument("--port", type=int, default=30000)
|
||
|
|
args = parser.parse_args()
|
||
|
|
|
||
|
|
asyncio.run(test_concurrent(args))
|
||
|
|
|
||
|
|
test_streaming(args)
|