"vscode:/vscode.git/clone" did not exist on "711f485643af9e6e9622d43caa8b020b6026bc15"
test_audio.py 12.9 KB
Newer Older
1
# SPDX-License-Identifier: Apache-2.0
2
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
3

4
5
import json

6
7
import openai
import pytest
8
import pytest_asyncio
9

10
11
from vllm.assets.audio import AudioAsset
from vllm.multimodal.utils import encode_audio_base64, fetch_audio
12

13
from ...utils import RemoteOpenAIServer
14

15
MODEL_NAME = "fixie-ai/ultravox-v0_5-llama-3_2-1b"
16
TEST_AUDIO_URLS = [
17
    AudioAsset("winning_call").url,
18
    AudioAsset("mary_had_lamb").url,
19
]
20
MAXIMUM_AUDIOS = 2
21
22


23
24
25
26
@pytest.fixture(scope="module")
def server():
    args = [
        "--max-model-len",
27
28
29
        "2048",
        "--max-num-seqs",
        "5",
30
        "--enforce-eager",
31
        "--trust-remote-code",
32
        "--limit-mm-per-prompt",
33
        json.dumps({"audio": MAXIMUM_AUDIOS}),
34
35
36
37
    ]

    with RemoteOpenAIServer(MODEL_NAME, args) as remote_server:
        yield remote_server
38
39


40
41
42
43
@pytest_asyncio.fixture
async def client(server):
    async with server.get_async_client() as async_client:
        yield async_client
44
45
46


@pytest.fixture(scope="session")
47
def base64_encoded_audio() -> dict[str, str]:
48
49
50
51
52
53
54
55
    return {
        audio_url: encode_audio_base64(*fetch_audio(audio_url))
        for audio_url in TEST_AUDIO_URLS
    }


@pytest.mark.asyncio
@pytest.mark.parametrize("model_name", [MODEL_NAME])
56
@pytest.mark.parametrize("audio_url", [TEST_AUDIO_URLS[0]])
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
async def test_single_chat_session_audio(client: openai.AsyncOpenAI,
                                         model_name: str, audio_url: str):
    messages = [{
        "role":
        "user",
        "content": [
            {
                "type": "audio_url",
                "audio_url": {
                    "url": audio_url
                }
            },
            {
                "type": "text",
                "text": "What's happening in this audio?"
            },
        ],
    }]

    # test single completion
77
78
79
80
81
    chat_completion = await client.chat.completions.create(
        model=model_name,
        messages=messages,
        max_completion_tokens=10,
        logprobs=True,
82
        temperature=0.0,
83
        top_logprobs=5)
84
85
86
87
88
    assert len(chat_completion.choices) == 1

    choice = chat_completion.choices[0]
    assert choice.finish_reason == "length"
    assert chat_completion.usage == openai.types.CompletionUsage(
89
        completion_tokens=10, prompt_tokens=202, total_tokens=212)
90
91
92
93
94
95
96
97
98
99
100
101

    message = choice.message
    message = chat_completion.choices[0].message
    assert message.content is not None and len(message.content) >= 10
    assert message.role == "assistant"
    messages.append({"role": "assistant", "content": message.content})

    # test multi-turn dialogue
    messages.append({"role": "user", "content": "express your result in json"})
    chat_completion = await client.chat.completions.create(
        model=model_name,
        messages=messages,
102
        max_completion_tokens=10,
103
104
105
106
107
    )
    message = chat_completion.choices[0].message
    assert message.content is not None and len(message.content) >= 0


108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
@pytest.mark.asyncio
@pytest.mark.parametrize("model_name", [MODEL_NAME])
@pytest.mark.parametrize("audio_url", [TEST_AUDIO_URLS[0]])
async def test_error_on_invalid_audio_url_type(client: openai.AsyncOpenAI,
                                               model_name: str,
                                               audio_url: str):
    messages = [{
        "role":
        "user",
        "content": [
            {
                "type": "audio_url",
                "audio_url": audio_url
            },
            {
                "type": "text",
                "text": "What's happening in this audio?"
            },
        ],
    }]

    # audio_url should be a dict {"url": "some url"}, not directly a string
    with pytest.raises(openai.BadRequestError):
        _ = await client.chat.completions.create(model=model_name,
                                                 messages=messages,
                                                 max_completion_tokens=10,
                                                 temperature=0.0)


137
138
@pytest.mark.asyncio
@pytest.mark.parametrize("model_name", [MODEL_NAME])
139
@pytest.mark.parametrize("audio_url", [TEST_AUDIO_URLS[0]])
140
141
async def test_single_chat_session_audio_base64encoded(
        client: openai.AsyncOpenAI, model_name: str, audio_url: str,
142
        base64_encoded_audio: dict[str, str]):
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162

    messages = [{
        "role":
        "user",
        "content": [
            {
                "type": "audio_url",
                "audio_url": {
                    "url":
                    f"data:audio/wav;base64,{base64_encoded_audio[audio_url]}"
                }
            },
            {
                "type": "text",
                "text": "What's happening in this audio?"
            },
        ],
    }]

    # test single completion
163
164
165
166
167
    chat_completion = await client.chat.completions.create(
        model=model_name,
        messages=messages,
        max_completion_tokens=10,
        logprobs=True,
168
        temperature=0.0,
169
        top_logprobs=5)
170
171
172
173
174
    assert len(chat_completion.choices) == 1

    choice = chat_completion.choices[0]
    assert choice.finish_reason == "length"
    assert chat_completion.usage == openai.types.CompletionUsage(
175
        completion_tokens=10, prompt_tokens=202, total_tokens=212)
176
177
178
179
180
181
182
183
184
185
186
187

    message = choice.message
    message = chat_completion.choices[0].message
    assert message.content is not None and len(message.content) >= 10
    assert message.role == "assistant"
    messages.append({"role": "assistant", "content": message.content})

    # test multi-turn dialogue
    messages.append({"role": "user", "content": "express your result in json"})
    chat_completion = await client.chat.completions.create(
        model=model_name,
        messages=messages,
188
        max_completion_tokens=10,
189
        temperature=0.0,
190
191
192
193
194
    )
    message = chat_completion.choices[0].message
    assert message.content is not None and len(message.content) >= 0


195
196
@pytest.mark.asyncio
@pytest.mark.parametrize("model_name", [MODEL_NAME])
197
@pytest.mark.parametrize("audio_url", [TEST_AUDIO_URLS[0]])
198
199
async def test_single_chat_session_input_audio(
        client: openai.AsyncOpenAI, model_name: str, audio_url: str,
200
        base64_encoded_audio: dict[str, str]):
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
    messages = [{
        "role":
        "user",
        "content": [
            {
                "type": "input_audio",
                "input_audio": {
                    "data": base64_encoded_audio[audio_url],
                    "format": "wav"
                }
            },
            {
                "type": "text",
                "text": "What's happening in this audio?"
            },
        ],
    }]

    # test single completion
    chat_completion = await client.chat.completions.create(
        model=model_name,
        messages=messages,
        max_completion_tokens=10,
        logprobs=True,
        top_logprobs=5)
    assert len(chat_completion.choices) == 1

    choice = chat_completion.choices[0]
    assert choice.finish_reason == "length"
    assert chat_completion.usage == openai.types.CompletionUsage(
231
        completion_tokens=10, prompt_tokens=202, total_tokens=212)
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249

    message = choice.message
    message = chat_completion.choices[0].message
    assert message.content is not None and len(message.content) >= 10
    assert message.role == "assistant"
    messages.append({"role": "assistant", "content": message.content})

    # test multi-turn dialogue
    messages.append({"role": "user", "content": "express your result in json"})
    chat_completion = await client.chat.completions.create(
        model=model_name,
        messages=messages,
        max_completion_tokens=10,
    )
    message = chat_completion.choices[0].message
    assert message.content is not None and len(message.content) >= 0


250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
@pytest.mark.asyncio
@pytest.mark.parametrize("model_name", [MODEL_NAME])
@pytest.mark.parametrize("audio_url", TEST_AUDIO_URLS)
async def test_chat_streaming_audio(client: openai.AsyncOpenAI,
                                    model_name: str, audio_url: str):
    messages = [{
        "role":
        "user",
        "content": [
            {
                "type": "audio_url",
                "audio_url": {
                    "url": audio_url
                }
            },
            {
                "type": "text",
                "text": "What's happening in this audio?"
            },
        ],
    }]

    # test single completion
    chat_completion = await client.chat.completions.create(
        model=model_name,
        messages=messages,
276
        max_completion_tokens=8,
277
278
279
280
281
282
283
284
285
        temperature=0.0,
    )
    output = chat_completion.choices[0].message.content
    stop_reason = chat_completion.choices[0].finish_reason

    # test streaming
    stream = await client.chat.completions.create(
        model=model_name,
        messages=messages,
286
        max_completion_tokens=8,
287
288
289
        temperature=0.0,
        stream=True,
    )
290
    chunks: list[str] = []
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
    finish_reason_count = 0
    async for chunk in stream:
        delta = chunk.choices[0].delta
        if delta.role:
            assert delta.role == "assistant"
        if delta.content:
            chunks.append(delta.content)
        if chunk.choices[0].finish_reason is not None:
            finish_reason_count += 1
    # finish reason should only return in last block
    assert finish_reason_count == 1
    assert chunk.choices[0].finish_reason == stop_reason
    assert delta.content
    assert "".join(chunks) == output


307
308
309
310
311
@pytest.mark.asyncio
@pytest.mark.parametrize("model_name", [MODEL_NAME])
@pytest.mark.parametrize("audio_url", TEST_AUDIO_URLS)
async def test_chat_streaming_input_audio(client: openai.AsyncOpenAI,
                                          model_name: str, audio_url: str,
312
                                          base64_encoded_audio: dict[str,
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
                                                                     str]):
    messages = [{
        "role":
        "user",
        "content": [
            {
                "type": "input_audio",
                "input_audio": {
                    "data": base64_encoded_audio[audio_url],
                    "format": "wav"
                }
            },
            {
                "type": "text",
                "text": "What's happening in this audio?"
            },
        ],
    }]

    # test single completion
    chat_completion = await client.chat.completions.create(
        model=model_name,
        messages=messages,
336
        max_completion_tokens=8,
337
338
339
340
341
342
343
344
345
        temperature=0.0,
    )
    output = chat_completion.choices[0].message.content
    stop_reason = chat_completion.choices[0].finish_reason

    # test streaming
    stream = await client.chat.completions.create(
        model=model_name,
        messages=messages,
346
        max_completion_tokens=8,
347
348
349
        temperature=0.0,
        stream=True,
    )
350
    chunks: list[str] = []
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
    finish_reason_count = 0
    async for chunk in stream:
        delta = chunk.choices[0].delta
        if delta.role:
            assert delta.role == "assistant"
        if delta.content:
            chunks.append(delta.content)
        if chunk.choices[0].finish_reason is not None:
            finish_reason_count += 1
    # finish reason should only return in last block
    assert finish_reason_count == 1
    assert chunk.choices[0].finish_reason == stop_reason
    assert delta.content
    assert "".join(chunks) == output


367
368
@pytest.mark.asyncio
@pytest.mark.parametrize("model_name", [MODEL_NAME])
369
370
@pytest.mark.parametrize(
    "audio_urls", [TEST_AUDIO_URLS, TEST_AUDIO_URLS + [TEST_AUDIO_URLS[0]]])
371
async def test_multi_audio_input(client: openai.AsyncOpenAI, model_name: str,
372
                                 audio_urls: list[str]):
373
374
375
376
377

    messages = [{
        "role":
        "user",
        "content": [
378
            *({
379
380
381
382
                "type": "audio_url",
                "audio_url": {
                    "url": audio_url
                }
383
            } for audio_url in audio_urls),
384
385
386
387
388
389
390
            {
                "type": "text",
                "text": "What's happening in this audio?"
            },
        ],
    }]

391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
    if len(audio_urls) > MAXIMUM_AUDIOS:
        with pytest.raises(openai.BadRequestError):  # test multi-audio input
            await client.chat.completions.create(
                model=model_name,
                messages=messages,
                max_completion_tokens=10,
                temperature=0.0,
            )

        # the server should still work afterwards
        completion = await client.completions.create(
            model=model_name,
            prompt=[0, 0, 0, 0, 0],
            max_tokens=5,
            temperature=0.0,
        )
        completion = completion.choices[0].text
        assert completion is not None and len(completion) >= 0
    else:
        chat_completion = await client.chat.completions.create(
411
412
            model=model_name,
            messages=messages,
413
            max_completion_tokens=10,
414
415
            temperature=0.0,
        )
416
417
        message = chat_completion.choices[0].message
        assert message.content is not None and len(message.content) >= 0