294 lines
9.9 KiB
Python
294 lines
9.9 KiB
Python
import base64
|
|
import io
|
|
import json
|
|
import os
|
|
import unittest
|
|
|
|
import numpy as np
|
|
import openai
|
|
import requests
|
|
from decord import VideoReader, cpu
|
|
from PIL import Image
|
|
|
|
from sglang.srt.utils import kill_child_process
|
|
from sglang.test.test_utils import (
|
|
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
|
|
DEFAULT_URL_FOR_TEST,
|
|
popen_launch_server,
|
|
)
|
|
|
|
|
|
class TestOpenAIVisionServer(unittest.TestCase):
|
|
@classmethod
|
|
def setUpClass(cls):
|
|
cls.model = "lmms-lab/llava-onevision-qwen2-0.5b-ov"
|
|
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=[
|
|
"--chat-template",
|
|
"chatml-llava",
|
|
# "--log-requests",
|
|
],
|
|
)
|
|
cls.base_url += "/v1"
|
|
|
|
@classmethod
|
|
def tearDownClass(cls):
|
|
kill_child_process(cls.process.pid)
|
|
|
|
def test_chat_completion(self):
|
|
client = openai.Client(api_key=self.api_key, base_url=self.base_url)
|
|
|
|
response = client.chat.completions.create(
|
|
model="default",
|
|
messages=[
|
|
{
|
|
"role": "user",
|
|
"content": [
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {
|
|
"url": "https://github.com/sgl-project/sglang/blob/main/test/lang/example_image.png?raw=true"
|
|
},
|
|
},
|
|
{
|
|
"type": "text",
|
|
"text": "Describe this image in a very short sentence.",
|
|
},
|
|
],
|
|
},
|
|
],
|
|
temperature=0,
|
|
)
|
|
|
|
assert response.choices[0].message.role == "assistant"
|
|
text = response.choices[0].message.content
|
|
assert isinstance(text, str)
|
|
assert "man" in text or "cab" in text, text
|
|
assert response.id
|
|
assert response.created
|
|
assert response.usage.prompt_tokens > 0
|
|
assert response.usage.completion_tokens > 0
|
|
assert response.usage.total_tokens > 0
|
|
|
|
def test_multi_turn_chat_completion(self):
|
|
client = openai.Client(api_key=self.api_key, base_url=self.base_url)
|
|
|
|
response = client.chat.completions.create(
|
|
model="default",
|
|
messages=[
|
|
{
|
|
"role": "user",
|
|
"content": [
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {
|
|
"url": "https://github.com/sgl-project/sglang/blob/main/test/lang/example_image.png?raw=true"
|
|
},
|
|
},
|
|
{
|
|
"type": "text",
|
|
"text": "Describe this image in a very short sentence.",
|
|
},
|
|
],
|
|
},
|
|
{
|
|
"role": "assistant",
|
|
"content": [
|
|
{
|
|
"type": "text",
|
|
"text": "There is a man at the back of a yellow cab ironing his clothes.",
|
|
}
|
|
],
|
|
},
|
|
{
|
|
"role": "user",
|
|
"content": [
|
|
{"type": "text", "text": "Repeat your previous answer."}
|
|
],
|
|
},
|
|
],
|
|
temperature=0,
|
|
)
|
|
|
|
assert response.choices[0].message.role == "assistant"
|
|
text = response.choices[0].message.content
|
|
assert isinstance(text, str)
|
|
assert "man" in text or "cab" in text, text
|
|
assert response.id
|
|
assert response.created
|
|
assert response.usage.prompt_tokens > 0
|
|
assert response.usage.completion_tokens > 0
|
|
assert response.usage.total_tokens > 0
|
|
|
|
def test_mult_images_chat_completion(self):
|
|
client = openai.Client(api_key=self.api_key, base_url=self.base_url)
|
|
|
|
response = client.chat.completions.create(
|
|
model="default",
|
|
messages=[
|
|
{
|
|
"role": "user",
|
|
"content": [
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {
|
|
"url": "https://raw.githubusercontent.com/sgl-project/sglang/main/test/lang/example_image.png"
|
|
},
|
|
"modalities": "multi-images",
|
|
},
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {
|
|
"url": "https://raw.githubusercontent.com/sgl-project/sglang/main/assets/logo.png"
|
|
},
|
|
"modalities": "multi-images",
|
|
},
|
|
{
|
|
"type": "text",
|
|
"text": "I have two very different images. They are not related at all. "
|
|
"Please describe the first image in one sentence, and then describe the second image in another sentence.",
|
|
},
|
|
],
|
|
},
|
|
],
|
|
temperature=0,
|
|
)
|
|
|
|
assert response.choices[0].message.role == "assistant"
|
|
text = response.choices[0].message.content
|
|
assert isinstance(text, str)
|
|
print(text)
|
|
assert "man" in text and "taxi" in text, text
|
|
assert "logo" in text, text
|
|
assert response.id
|
|
assert response.created
|
|
assert response.usage.prompt_tokens > 0
|
|
assert response.usage.completion_tokens > 0
|
|
assert response.usage.total_tokens > 0
|
|
|
|
def prepare_video_messages(self, video_path):
|
|
max_frames_num = 32
|
|
vr = VideoReader(video_path, ctx=cpu(0))
|
|
total_frame_num = len(vr)
|
|
uniform_sampled_frames = np.linspace(
|
|
0, total_frame_num - 1, max_frames_num, dtype=int
|
|
)
|
|
frame_idx = uniform_sampled_frames.tolist()
|
|
frames = vr.get_batch(frame_idx).asnumpy()
|
|
|
|
base64_frames = []
|
|
for frame in frames:
|
|
pil_img = Image.fromarray(frame)
|
|
buff = io.BytesIO()
|
|
pil_img.save(buff, format="JPEG")
|
|
base64_str = base64.b64encode(buff.getvalue()).decode("utf-8")
|
|
base64_frames.append(base64_str)
|
|
|
|
messages = [{"role": "user", "content": []}]
|
|
frame_format = {
|
|
"type": "image_url",
|
|
"image_url": {"url": "data:image/jpeg;base64,{}"},
|
|
"modalities": "video",
|
|
}
|
|
|
|
for base64_frame in base64_frames:
|
|
frame_format["image_url"]["url"] = "data:image/jpeg;base64,{}".format(
|
|
base64_frame
|
|
)
|
|
messages[0]["content"].append(frame_format.copy())
|
|
|
|
prompt = {"type": "text", "text": "Please describe the video in detail."}
|
|
messages[0]["content"].append(prompt)
|
|
|
|
return messages
|
|
|
|
def test_video_chat_completion(self):
|
|
url = "https://raw.githubusercontent.com/EvolvingLMMs-Lab/sglang/dev/onevision_local/assets/jobs.mp4"
|
|
cache_dir = os.path.expanduser("~/.cache")
|
|
file_path = os.path.join(cache_dir, "jobs.mp4")
|
|
os.makedirs(cache_dir, exist_ok=True)
|
|
|
|
if not os.path.exists(file_path):
|
|
response = requests.get(url)
|
|
response.raise_for_status()
|
|
|
|
with open(file_path, "wb") as f:
|
|
f.write(response.content)
|
|
|
|
client = openai.Client(api_key=self.api_key, base_url=self.base_url)
|
|
|
|
messages = self.prepare_video_messages(file_path)
|
|
|
|
video_request = client.chat.completions.create(
|
|
model="default",
|
|
messages=messages,
|
|
temperature=0,
|
|
max_tokens=1024,
|
|
stream=True,
|
|
)
|
|
|
|
print("-" * 30)
|
|
video_response = ""
|
|
for chunk in video_request:
|
|
if chunk.choices[0].delta.content is not None:
|
|
content = chunk.choices[0].delta.content
|
|
video_response += content
|
|
print(content, end="", flush=True)
|
|
print("-" * 30)
|
|
|
|
# Add assertions to validate the video response
|
|
self.assertIsNotNone(video_response)
|
|
self.assertGreater(len(video_response), 0)
|
|
|
|
def test_regex(self):
|
|
client = openai.Client(api_key=self.api_key, base_url=self.base_url)
|
|
|
|
regex = (
|
|
r"""\{\n"""
|
|
+ r""" "color": "[\w]+",\n"""
|
|
+ r""" "number_of_cars": [\d]+\n"""
|
|
+ r"""\}"""
|
|
)
|
|
|
|
response = client.chat.completions.create(
|
|
model="default",
|
|
messages=[
|
|
{
|
|
"role": "user",
|
|
"content": [
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {
|
|
"url": "https://github.com/sgl-project/sglang/blob/main/test/lang/example_image.png?raw=true"
|
|
},
|
|
},
|
|
{
|
|
"type": "text",
|
|
"text": "Describe this image in the JSON format.",
|
|
},
|
|
],
|
|
},
|
|
],
|
|
temperature=0,
|
|
extra_body={"regex": regex},
|
|
)
|
|
text = response.choices[0].message.content
|
|
|
|
try:
|
|
js_obj = json.loads(text)
|
|
except (TypeError, json.decoder.JSONDecodeError):
|
|
print("JSONDecodeError", text)
|
|
raise
|
|
assert isinstance(js_obj["color"], str)
|
|
assert isinstance(js_obj["number_of_cars"], int)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|