test_vision_openai_server_common.py 18.2 KB
Newer Older
1
2
import base64
import io
Ying Sheng's avatar
Ying Sheng committed
3
import json
4
import os
5
from concurrent.futures import ThreadPoolExecutor
Ying Sheng's avatar
Ying Sheng committed
6

7
import numpy as np
Ying Sheng's avatar
Ying Sheng committed
8
import openai
9
10
import requests
from PIL import Image
Ying Sheng's avatar
Ying Sheng committed
11

12
from sglang.srt.utils import kill_process_tree
13
14
15
from sglang.test.test_utils import (
    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
    DEFAULT_URL_FOR_TEST,
16
    CustomTestCase,
17
18
    popen_launch_server,
)
Ying Sheng's avatar
Ying Sheng committed
19

20
21
22
23
24
25
26
27
28
29
30
# image
IMAGE_MAN_IRONING_URL = "https://raw.githubusercontent.com/sgl-project/sgl-test-files/refs/heads/main/images/man_ironing_on_back_of_suv.png"
IMAGE_SGL_LOGO_URL = "https://raw.githubusercontent.com/sgl-project/sgl-test-files/refs/heads/main/images/sgl_logo.png"

# video
VIDEO_JOBS_URL = "https://raw.githubusercontent.com/sgl-project/sgl-test-files/refs/heads/main/videos/jobs_presenting_ipod.mp4"

# audio
AUDIO_TRUMP_SPEECH_URL = "https://raw.githubusercontent.com/sgl-project/sgl-test-files/refs/heads/main/audios/Trump_WEF_2018_10s.mp3"
AUDIO_BIRD_SONG_URL = "https://raw.githubusercontent.com/sgl-project/sgl-test-files/refs/heads/main/audios/bird_song.mp3"

Ying Sheng's avatar
Ying Sheng committed
31

32
class TestOpenAIVisionServer(CustomTestCase):
Ying Sheng's avatar
Ying Sheng committed
33
34
    @classmethod
    def setUpClass(cls):
35
        cls.model = "lmms-lab/llava-onevision-qwen2-0.5b-ov"
36
        cls.base_url = DEFAULT_URL_FOR_TEST
Ying Sheng's avatar
Ying Sheng committed
37
38
39
40
        cls.api_key = "sk-123456"
        cls.process = popen_launch_server(
            cls.model,
            cls.base_url,
41
            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
Ying Sheng's avatar
Ying Sheng committed
42
43
44
45
46
47
            api_key=cls.api_key,
        )
        cls.base_url += "/v1"

    @classmethod
    def tearDownClass(cls):
48
        kill_process_tree(cls.process.pid)
Ying Sheng's avatar
Ying Sheng committed
49

50
51
52
53
54
55
    def get_audio_request_kwargs(self):
        return self.get_request_kwargs()

    def get_vision_request_kwargs(self):
        return self.get_request_kwargs()

56
57
58
    def get_request_kwargs(self):
        return {}

59
    def test_single_image_chat_completion(self):
Ying Sheng's avatar
Ying Sheng committed
60
61
62
63
64
65
66
67
68
69
        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",
70
                            "image_url": {"url": IMAGE_MAN_IRONING_URL},
Ying Sheng's avatar
Ying Sheng committed
71
                        },
Ying Sheng's avatar
Ying Sheng committed
72
73
74
75
                        {
                            "type": "text",
                            "text": "Describe this image in a very short sentence.",
                        },
Ying Sheng's avatar
Ying Sheng committed
76
77
78
79
                    ],
                },
            ],
            temperature=0,
80
            **(self.get_vision_request_kwargs()),
Ying Sheng's avatar
Ying Sheng committed
81
82
83
        )

        assert response.choices[0].message.role == "assistant"
Ying Sheng's avatar
Ying Sheng committed
84
85
        text = response.choices[0].message.content
        assert isinstance(text, str)
86
        # `driver` is for gemma-3-it
87
88
89
90
91
92
93
94
95
96
        assert (
            "man" in text or "person" or "driver" in text
        ), f"text: {text}, should contain man, person or driver"
        assert (
            "cab" in text
            or "taxi" in text
            or "SUV" in text
            or "vehicle" in text
            or "car" in text
        ), f"text: {text}, should contain cab, taxi, SUV, vehicle or car"
Mick's avatar
Mick committed
97
        # MiniCPMO fails to recognize `iron`, but `hanging`
98
99
100
        assert (
            "iron" in text or "hang" in text or "cloth" in text or "holding" in text
        ), f"text: {text}, should contain iron, hang, cloth or holding"
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
        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",
118
                            "image_url": {"url": IMAGE_MAN_IRONING_URL},
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
                        },
                        {
                            "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,
143
            **(self.get_vision_request_kwargs()),
144
145
146
147
148
        )

        assert response.choices[0].message.role == "assistant"
        text = response.choices[0].message.content
        assert isinstance(text, str)
149
150
151
        assert (
            "man" in text or "cab" in text
        ), f"text: {text}, should contain man or cab"
Ying Sheng's avatar
Ying Sheng committed
152
153
154
155
        assert response.id
        assert response.created
        assert response.usage.prompt_tokens > 0
        assert response.usage.completion_tokens > 0
156
157
        assert response.usage.total_tokens > 0

158
    def test_multi_images_chat_completion(self):
159
160
161
162
163
164
165
166
167
168
        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",
Mick's avatar
Mick committed
169
                            "image_url": {"url": IMAGE_MAN_IRONING_URL},
170
                            "modalities": "multi-images",
171
172
173
                        },
                        {
                            "type": "image_url",
174
                            "image_url": {"url": IMAGE_SGL_LOGO_URL},
175
                            "modalities": "multi-images",
176
177
178
                        },
                        {
                            "type": "text",
179
180
                            "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.",
181
182
183
184
185
                        },
                    ],
                },
            ],
            temperature=0,
186
            **(self.get_vision_request_kwargs()),
187
188
189
190
191
        )

        assert response.choices[0].message.role == "assistant"
        text = response.choices[0].message.content
        assert isinstance(text, str)
Mick's avatar
Mick committed
192
193
194
        print("-" * 30)
        print(f"Multi images response:\n{text}")
        print("-" * 30)
195
196
197
198
199
200
        assert (
            "man" in text or "cab" in text or "SUV" in text or "taxi" in text
        ), f"text: {text}, should contain man, cab, SUV or taxi"
        assert (
            "logo" in text or '"S"' in text or "SG" in text
        ), f"text: {text}, should contain logo, S or SG"
201
202
203
204
        assert response.id
        assert response.created
        assert response.usage.prompt_tokens > 0
        assert response.usage.completion_tokens > 0
Ying Sheng's avatar
Ying Sheng committed
205
206
        assert response.usage.total_tokens > 0

207
    def prepare_video_images_messages(self, video_path):
208
209
        # the memory consumed by the Vision Attention varies a lot, e.g. blocked qkv vs full-sequence sdpa
        # the size of the video embeds differs from the `modality` argument when preprocessed
210
211
212
213
214
215
216

        # We import decord here to avoid a strange Segmentation fault (core dumped) issue.
        # The following import order will cause Segmentation fault.
        # import decord
        # from transformers import AutoTokenizer
        from decord import VideoReader, cpu

217
        max_frames_num = 10
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
        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,{}"},
238
            "modalities": "image",
239
240
241
242
243
244
245
246
247
248
249
250
251
        }

        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

252
    def prepare_video_messages(self, video_path):
253
254
255
256
257
        messages = [
            {
                "role": "user",
                "content": [
                    {
258
259
                        "type": "video_url",
                        "video_url": {"url": f"{video_path}"},
260
261
262
263
264
265
266
                    },
                    {"type": "text", "text": "Please describe the video in detail."},
                ],
            },
        ]
        return messages

267
    def get_or_download_file(self, url: str) -> str:
268
        cache_dir = os.path.expanduser("~/.cache")
269
270
271
272
        if url is None:
            raise ValueError()
        file_name = url.split("/")[-1]
        file_path = os.path.join(cache_dir, file_name)
273
274
275
276
277
278
279
280
        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)
281
282
        return file_path

283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
    # this test samples frames of video as input, but not video directly
    def test_video_images_chat_completion(self):
        url = VIDEO_JOBS_URL
        file_path = self.get_or_download_file(url)

        client = openai.Client(api_key=self.api_key, base_url=self.base_url)

        messages = self.prepare_video_images_messages(file_path)

        response = client.chat.completions.create(
            model="default",
            messages=messages,
            temperature=0,
            max_tokens=1024,
            stream=False,
        )

        video_response = response.choices[0].message.content

        print("-" * 30)
        print(f"Video images response:\n{video_response}")
        print("-" * 30)

        # Add assertions to validate the video response
        assert (
            "iPod" in video_response
            or "device" in video_response
            or "microphone" in video_response
        ), video_response
        assert (
            "man" in video_response
            or "person" in video_response
            or "individual" in video_response
            or "speaker" in video_response
        ), video_response
        assert (
            "present" in video_response
            or "examine" in video_response
            or "display" in video_response
            or "hold" in video_response
        )
        assert "black" in video_response or "dark" in video_response
        self.assertIsNotNone(video_response)
        self.assertGreater(len(video_response), 0)

    def _test_video_chat_completion(self):
329
330
        url = VIDEO_JOBS_URL
        file_path = self.get_or_download_file(url)
331
332
333
334
335

        client = openai.Client(api_key=self.api_key, base_url=self.base_url)

        messages = self.prepare_video_messages(file_path)

Mick's avatar
Mick committed
336
        response = client.chat.completions.create(
337
338
339
340
            model="default",
            messages=messages,
            temperature=0,
            max_tokens=1024,
Mick's avatar
Mick committed
341
            stream=False,
342
            **(self.get_vision_request_kwargs()),
343
        )
344

Mick's avatar
Mick committed
345
346
        video_response = response.choices[0].message.content

347
        print("-" * 30)
Mick's avatar
Mick committed
348
        print(f"Video response:\n{video_response}")
349
350
351
        print("-" * 30)

        # Add assertions to validate the video response
352
        assert (
353
354
355
            "iPod" in video_response
            or "device" in video_response
            or "microphone" in video_response
356
        ), f"video_response: {video_response}, should contain 'iPod' or 'device'"
Mick's avatar
Mick committed
357
358
359
360
        assert (
            "man" in video_response
            or "person" in video_response
            or "individual" in video_response
361
            or "speaker" in video_response
362
        ), f"video_response: {video_response}, should either have 'man' in video_response, or 'person' in video_response, or 'individual' in video_response or 'speaker' in video_response"
Mick's avatar
Mick committed
363
364
365
366
        assert (
            "present" in video_response
            or "examine" in video_response
            or "display" in video_response
367
            or "hold" in video_response
368
369
370
371
        ), f"video_response: {video_response}, should contain 'present', 'examine', 'display', or 'hold'"
        assert (
            "black" in video_response or "dark" in video_response
        ), f"video_response: {video_response}, should contain 'black' or 'dark'"
372
373
374
        self.assertIsNotNone(video_response)
        self.assertGreater(len(video_response), 0)

Ying Sheng's avatar
Ying Sheng committed
375
376
377
378
    def test_regex(self):
        client = openai.Client(api_key=self.api_key, base_url=self.base_url)

        regex = (
379
380
381
            r"""\{"""
            + r""""color":"[\w]+","""
            + r""""number_of_cars":[\d]+"""
Ying Sheng's avatar
Ying Sheng committed
382
383
384
            + r"""\}"""
        )

385
        extra_kwargs = self.get_vision_request_kwargs()
386
387
        extra_kwargs.setdefault("extra_body", {})["regex"] = regex

Ying Sheng's avatar
Ying Sheng committed
388
389
390
391
392
393
394
395
        response = client.chat.completions.create(
            model="default",
            messages=[
                {
                    "role": "user",
                    "content": [
                        {
                            "type": "image_url",
396
                            "image_url": {"url": IMAGE_MAN_IRONING_URL},
Ying Sheng's avatar
Ying Sheng committed
397
398
399
400
401
402
403
404
405
                        },
                        {
                            "type": "text",
                            "text": "Describe this image in the JSON format.",
                        },
                    ],
                },
            ],
            temperature=0,
406
            **extra_kwargs,
Ying Sheng's avatar
Ying Sheng committed
407
408
409
410
411
412
413
414
415
416
417
        )
        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)

418
419
420
421
422
423
424
425
    def run_decode_with_image(self, image_id):
        client = openai.Client(api_key=self.api_key, base_url=self.base_url)

        content = []
        if image_id == 0:
            content.append(
                {
                    "type": "image_url",
426
                    "image_url": {"url": IMAGE_MAN_IRONING_URL},
427
428
429
430
431
432
                }
            )
        elif image_id == 1:
            content.append(
                {
                    "type": "image_url",
433
                    "image_url": {"url": IMAGE_SGL_LOGO_URL},
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
                }
            )
        else:
            pass

        content.append(
            {
                "type": "text",
                "text": "Describe this image in a very short sentence.",
            }
        )

        response = client.chat.completions.create(
            model="default",
            messages=[
                {"role": "user", "content": content},
            ],
            temperature=0,
452
            **(self.get_vision_request_kwargs()),
453
454
455
456
457
458
459
460
461
462
463
        )

        assert response.choices[0].message.role == "assistant"
        text = response.choices[0].message.content
        assert isinstance(text, str)

    def test_mixed_batch(self):
        image_ids = [0, 1, 2] * 4
        with ThreadPoolExecutor(4) as executor:
            list(executor.map(self.run_decode_with_image, image_ids))

Mick's avatar
Mick committed
464
465
466
467
468
469
470
471
472
    def prepare_audio_messages(self, prompt, audio_file_name):
        messages = [
            {
                "role": "user",
                "content": [
                    {
                        "type": "audio_url",
                        "audio_url": {"url": f"{audio_file_name}"},
                    },
Mick's avatar
Mick committed
473
474
475
476
                    {
                        "type": "text",
                        "text": prompt,
                    },
Mick's avatar
Mick committed
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
                ],
            }
        ]

        return messages

    def get_audio_response(self, url: str, prompt, category):
        audio_file_path = self.get_or_download_file(url)
        client = openai.Client(api_key="sk-123456", base_url=self.base_url)

        messages = self.prepare_audio_messages(prompt, audio_file_path)

        response = client.chat.completions.create(
            model="default",
            messages=messages,
            temperature=0,
            max_tokens=128,
            stream=False,
495
            **(self.get_audio_request_kwargs()),
Mick's avatar
Mick committed
496
497
498
499
500
501
502
503
504
505
506
507
508
        )

        audio_response = response.choices[0].message.content

        print("-" * 30)
        print(f"audio {category} response:\n{audio_response}")
        print("-" * 30)

        audio_response = audio_response.lower()

        self.assertIsNotNone(audio_response)
        self.assertGreater(len(audio_response), 0)

509
        return audio_response.lower()
Mick's avatar
Mick committed
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534

    def _test_audio_speech_completion(self):
        # a fragment of Trump's speech
        audio_response = self.get_audio_response(
            AUDIO_TRUMP_SPEECH_URL,
            "I have an audio sample. Please repeat the person's words",
            category="speech",
        )
        assert "thank you" in audio_response
        assert "it's a privilege to be here" in audio_response
        assert "leader" in audio_response
        assert "science" in audio_response
        assert "art" in audio_response

    def _test_audio_ambient_completion(self):
        # bird song
        audio_response = self.get_audio_response(
            AUDIO_BIRD_SONG_URL,
            "Please listen to the audio snippet carefully and transcribe the content.",
            "ambient",
        )
        assert "bird" in audio_response

    def test_audio_chat_completion(self):
        pass