test_vision_openai_server_common.py 19.4 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
                        {
                            "type": "text",
74
                            "text": "Describe this image in a sentence.",
Ying Sheng's avatar
Ying Sheng committed
75
                        },
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
        assert (
99
100
101
102
103
104
105
            "iron" in text
            or "hang" in text
            or "cloth" in text
            or "coat" in text
            or "holding" in text
            or "outfit" in text
        ), f"text: {text}, should contain iron, hang, cloth, coat or holding or outfit"
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
        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",
123
                            "image_url": {"url": IMAGE_MAN_IRONING_URL},
124
125
126
                        },
                        {
                            "type": "text",
127
                            "text": "Describe this image in a sentence.",
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
                        },
                    ],
                },
                {
                    "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,
148
            **(self.get_vision_request_kwargs()),
149
150
151
152
153
        )

        assert response.choices[0].message.role == "assistant"
        text = response.choices[0].message.content
        assert isinstance(text, str)
154
155
156
        assert (
            "man" in text or "cab" in text
        ), f"text: {text}, should contain man or cab"
Ying Sheng's avatar
Ying Sheng committed
157
158
159
160
        assert response.id
        assert response.created
        assert response.usage.prompt_tokens > 0
        assert response.usage.completion_tokens > 0
161
162
        assert response.usage.total_tokens > 0

163
    def test_multi_images_chat_completion(self):
164
165
166
167
168
169
170
171
172
173
        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
174
                            "image_url": {"url": IMAGE_MAN_IRONING_URL},
175
                            "modalities": "multi-images",
176
177
178
                        },
                        {
                            "type": "image_url",
179
                            "image_url": {"url": IMAGE_SGL_LOGO_URL},
180
                            "modalities": "multi-images",
181
182
183
                        },
                        {
                            "type": "text",
184
185
                            "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.",
186
187
188
189
190
                        },
                    ],
                },
            ],
            temperature=0,
191
            **(self.get_vision_request_kwargs()),
192
193
194
195
196
        )

        assert response.choices[0].message.role == "assistant"
        text = response.choices[0].message.content
        assert isinstance(text, str)
Mick's avatar
Mick committed
197
198
199
        print("-" * 30)
        print(f"Multi images response:\n{text}")
        print("-" * 30)
200
        assert (
201
202
203
204
205
206
            "man" in text
            or "cab" in text
            or "SUV" in text
            or "taxi" in text
            or "car" in text
        ), f"text: {text}, should contain man, cab, SUV, taxi or car"
207
        assert (
208
209
            "logo" in text or '"S"' in text or "SG" in text or "graphic" in text
        ), f"text: {text}, should contain logo, S or SG or graphic"
210
211
212
213
        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
214
215
        assert response.usage.total_tokens > 0

216
    def prepare_video_images_messages(self, video_path):
217
218
        # 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
219
220
221
222
223
224
225

        # 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

226
        max_frames_num = 10
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
        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,{}"},
247
            "modalities": "image",
248
249
250
251
252
253
254
255
256
257
258
259
260
        }

        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

261
    def prepare_video_messages(self, video_path):
262
263
264
265
266
        messages = [
            {
                "role": "user",
                "content": [
                    {
267
268
                        "type": "video_url",
                        "video_url": {"url": f"{video_path}"},
269
270
271
272
273
274
275
                    },
                    {"type": "text", "text": "Please describe the video in detail."},
                ],
            },
        ]
        return messages

276
    def get_or_download_file(self, url: str) -> str:
277
        cache_dir = os.path.expanduser("~/.cache")
278
279
280
281
        if url is None:
            raise ValueError()
        file_name = url.split("/")[-1]
        file_path = os.path.join(cache_dir, file_name)
282
283
284
285
286
287
288
289
        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)
290
291
        return file_path

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
    # 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
320
321
322
323
324
325
        ), f"""
        ====================== video_response =====================
        {video_response}
        ===========================================================
        should contain 'iPod' or 'device' or 'microphone'
        """
326
327
328
329
330
        assert (
            "man" in video_response
            or "person" in video_response
            or "individual" in video_response
            or "speaker" in video_response
331
            or "presenter" in video_response
332
            or "Steve" in video_response
333
            or "hand" in video_response
334
335
336
337
        ), f"""
        ====================== video_response =====================
        {video_response}
        ===========================================================
338
        should contain 'man' or 'person' or 'individual' or 'speaker' or 'presenter' or 'Steve' or 'hand'
339
        """
340
341
342
343
344
        assert (
            "present" in video_response
            or "examine" in video_response
            or "display" in video_response
            or "hold" in video_response
345
346
347
348
349
350
        ), f"""
        ====================== video_response =====================
        {video_response}
        ===========================================================
        should contain 'present' or 'examine' or 'display' or 'hold'
        """
351
352
353
354
        self.assertIsNotNone(video_response)
        self.assertGreater(len(video_response), 0)

    def _test_video_chat_completion(self):
355
356
        url = VIDEO_JOBS_URL
        file_path = self.get_or_download_file(url)
357
358
359
360
361

        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
362
        response = client.chat.completions.create(
363
364
365
366
            model="default",
            messages=messages,
            temperature=0,
            max_tokens=1024,
Mick's avatar
Mick committed
367
            stream=False,
368
            **(self.get_vision_request_kwargs()),
369
        )
370

Mick's avatar
Mick committed
371
372
        video_response = response.choices[0].message.content

373
        print("-" * 30)
Mick's avatar
Mick committed
374
        print(f"Video response:\n{video_response}")
375
376
377
        print("-" * 30)

        # Add assertions to validate the video response
378
        assert (
379
380
381
            "iPod" in video_response
            or "device" in video_response
            or "microphone" in video_response
382
        ), f"video_response: {video_response}, should contain 'iPod' or 'device'"
Mick's avatar
Mick committed
383
384
385
386
        assert (
            "man" in video_response
            or "person" in video_response
            or "individual" in video_response
387
            or "speaker" in video_response
388
            or "presenter" in video_response
389
            or "hand" in video_response
390
        ), 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 or 'presenter' or 'hand' in video_response"
Mick's avatar
Mick committed
391
392
393
394
        assert (
            "present" in video_response
            or "examine" in video_response
            or "display" in video_response
395
            or "hold" in video_response
396
397
398
399
        ), 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'"
400
401
402
        self.assertIsNotNone(video_response)
        self.assertGreater(len(video_response), 0)

Ying Sheng's avatar
Ying Sheng committed
403
404
405
406
    def test_regex(self):
        client = openai.Client(api_key=self.api_key, base_url=self.base_url)

        regex = (
407
408
409
            r"""\{"""
            + r""""color":"[\w]+","""
            + r""""number_of_cars":[\d]+"""
Ying Sheng's avatar
Ying Sheng committed
410
411
412
            + r"""\}"""
        )

413
        extra_kwargs = self.get_vision_request_kwargs()
414
415
        extra_kwargs.setdefault("extra_body", {})["regex"] = regex

Ying Sheng's avatar
Ying Sheng committed
416
417
418
419
420
421
422
423
        response = client.chat.completions.create(
            model="default",
            messages=[
                {
                    "role": "user",
                    "content": [
                        {
                            "type": "image_url",
424
                            "image_url": {"url": IMAGE_MAN_IRONING_URL},
Ying Sheng's avatar
Ying Sheng committed
425
426
427
428
429
430
431
432
433
                        },
                        {
                            "type": "text",
                            "text": "Describe this image in the JSON format.",
                        },
                    ],
                },
            ],
            temperature=0,
434
            **extra_kwargs,
Ying Sheng's avatar
Ying Sheng committed
435
436
437
438
439
440
441
442
443
444
445
        )
        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)

446
447
448
449
450
451
452
453
    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",
454
                    "image_url": {"url": IMAGE_MAN_IRONING_URL},
455
456
457
458
459
460
                }
            )
        elif image_id == 1:
            content.append(
                {
                    "type": "image_url",
461
                    "image_url": {"url": IMAGE_SGL_LOGO_URL},
462
463
464
465
466
467
468
469
                }
            )
        else:
            pass

        content.append(
            {
                "type": "text",
470
                "text": "Describe this image in a sentence.",
471
472
473
474
475
476
477
478
479
            }
        )

        response = client.chat.completions.create(
            model="default",
            messages=[
                {"role": "user", "content": content},
            ],
            temperature=0,
480
            **(self.get_vision_request_kwargs()),
481
482
483
484
485
486
487
488
489
490
491
        )

        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
492
493
494
495
496
497
498
499
500
    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
501
502
503
504
                    {
                        "type": "text",
                        "text": prompt,
                    },
Mick's avatar
Mick committed
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
                ],
            }
        ]

        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,
523
            **(self.get_audio_request_kwargs()),
Mick's avatar
Mick committed
524
525
526
527
528
529
530
531
532
533
534
535
536
        )

        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)

537
        return audio_response.lower()
Mick's avatar
Mick committed
538
539
540
541
542

    def _test_audio_speech_completion(self):
        # a fragment of Trump's speech
        audio_response = self.get_audio_response(
            AUDIO_TRUMP_SPEECH_URL,
543
            "Listen to this audio and write down the audio transcription in English.",
Mick's avatar
Mick committed
544
545
            category="speech",
        )
546
547
548
549
550
551
552
553
554
555
556
        check_list = [
            "thank you",
            "it's a privilege to be here",
            "leader",
            "science",
            "art",
        ]
        for check_word in check_list:
            assert (
                check_word in audio_response
            ), f"audio_response: |{audio_response}| should contain |{check_word}|"
Mick's avatar
Mick committed
557
558
559
560
561

    def _test_audio_ambient_completion(self):
        # bird song
        audio_response = self.get_audio_response(
            AUDIO_BIRD_SONG_URL,
562
            "Please listen to the audio snippet carefully and transcribe the content in English.",
Mick's avatar
Mick committed
563
564
565
566
567
568
            "ambient",
        )
        assert "bird" in audio_response

    def test_audio_chat_completion(self):
        pass