test_httpserver_llava.py 2.63 KB
Newer Older
Lianmin Zheng's avatar
Lianmin Zheng committed
1
"""
2
Usage:
Lianmin Zheng's avatar
Lianmin Zheng committed
3
python3 -m sglang.launch_server --model-path liuhaotian/llava-v1.5-7b --tokenizer-path llava-hf/llava-1.5-7b-hf --port 30000
4
python3 test_httpserver_llava.py
Lianmin Zheng's avatar
Lianmin Zheng committed
5
6
7
8
9
10
11
12

Output:
The image features a man standing on the back of a yellow taxi cab, holding
"""

import argparse
import asyncio
import json
13
import time
Lianmin Zheng's avatar
Lianmin Zheng committed
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36

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:",
37
                    "image_data": "test_image.png",
Lianmin Zheng's avatar
Lianmin Zheng committed
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
                    "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:",
58
            "image_data": "test_image.png",
Lianmin Zheng's avatar
Lianmin Zheng committed
59
60
61
62
63
64
65
66
67
68
            "sampling_params": {
                "temperature": 0,
                "max_new_tokens": 128,
            },
            "stream": True,
        },
        stream=True,
    )

    prev = 0
69
70
71
72
73
74
    for chunk in response.iter_lines(decode_unicode=False):
        chunk = chunk.decode("utf-8")
        if chunk and chunk.startswith("data:"):
            if chunk == "data: [DONE]":
                break
            data = json.loads(chunk[5:].strip("\n"))
Lianmin Zheng's avatar
Lianmin Zheng committed
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
            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)