test_sglang.py 11.8 KB
Newer Older
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
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
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
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
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
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
276
277
278
279
280
281
282
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
# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0

import logging
import os
import shutil
import time

import pytest

from tests.fault_tolerance.cancellation.utils import (
    DynamoFrontendProcess,
    poll_for_pattern,
    read_streaming_responses,
    send_cancellable_request,
)
from tests.utils.constants import FAULT_TOLERANCE_MODEL_NAME
from tests.utils.engine_process import FRONTEND_PORT
from tests.utils.managed_process import ManagedProcess
from tests.utils.payloads import check_health_generate, check_models_api

logger = logging.getLogger(__name__)


class DynamoWorkerProcess(ManagedProcess):
    """Process manager for Dynamo worker with SGLang backend"""

    def __init__(self, request, mode: str = "agg"):
        """
        Initialize SGLang worker process.

        Args:
            request: pytest request object
            mode: One of "agg", "prefill", "decode"
        """
        command = [
            "python3",
            "-m",
            "dynamo.sglang",
            "--model-path",
            FAULT_TOLERANCE_MODEL_NAME,
            "--served-model-name",
            FAULT_TOLERANCE_MODEL_NAME,
            "--page-size",
            "16",
            "--tp",
            "1",
            "--trust-remote-code",
        ]

        # Add mode-specific arguments
        if mode == "agg":
            # Aggregated mode - add skip-tokenizer-init like the serve test
            command.append("--skip-tokenizer-init")
        else:
            # Disaggregated mode - add disaggregation arguments like disagg.sh
            command.extend(
                [
                    "--disaggregation-mode",
                    mode,
                    "--disaggregation-bootstrap-port",
                    "12345",
                    "--host",
                    "0.0.0.0",
                    "--disaggregation-transfer-backend",
                    "nixl",
                ]
            )

        health_check_urls = [
            (f"http://localhost:{FRONTEND_PORT}/v1/models", check_models_api),
            (f"http://localhost:{FRONTEND_PORT}/health", check_health_generate),
        ]

        # Set port based on worker type
        if mode == "prefill":
            port = "8082"
            health_check_urls = [(f"http://localhost:{port}/health", self.is_ready)]
        elif mode == "decode":
            port = "8081"
            health_check_urls = [(f"http://localhost:{port}/health", self.is_ready)]
        else:  # agg (aggregated mode)
            port = "8081"

        # Set debug logging environment
        env = os.environ.copy()
        env["DYN_LOG"] = "debug"
        env["DYN_SYSTEM_USE_ENDPOINT_HEALTH_STATUS"] = '["generate"]'
        env["DYN_SYSTEM_PORT"] = port

        # Set GPU assignment for disaggregated mode (like disagg.sh)
        if mode == "decode":
            env["CUDA_VISIBLE_DEVICES"] = "1"  # Use GPU 1 for decode worker
        elif mode == "prefill":
            env["CUDA_VISIBLE_DEVICES"] = "0"  # Use GPU 0 for prefill worker
        # For agg (aggregated) mode, use default GPU assignment

        # Set log directory based on worker type
        log_dir = f"{request.node.name}_{mode}_worker"

        # Clean up any existing log directory from previous runs
        try:
            shutil.rmtree(log_dir)
            logger.info(f"Cleaned up existing log directory: {log_dir}")
        except FileNotFoundError:
            # Directory doesn't exist, which is fine
            pass

        super().__init__(
            command=command,
            env=env,
            health_check_urls=health_check_urls,
            timeout=300,
            display_output=True,
            terminate_existing=False,
            # Ensure any orphaned SGLang engine cores or child helpers are cleaned up
            stragglers=[
                "SGLANG:EngineCore",
            ],
            straggler_commands=[
                "-m dynamo.sglang",
            ],
            log_dir=log_dir,
        )

        self.mode = mode

    def get_pid(self):
        """Get the PID of the worker process"""
        return self.proc.pid if self.proc else None

    def is_ready(self, response) -> bool:
        """Check the health of the worker process"""
        try:
            data = response.json()
            if data.get("status") == "ready":
                logger.info(f"{self.mode.capitalize()} worker status is ready")
                return True
            logger.warning(
                f"{self.mode.capitalize()} worker status is not ready: {data.get('status')}"
            )
        except ValueError:
            logger.warning(
                f"{self.mode.capitalize()} worker health response is not valid JSON"
            )
        return False


@pytest.mark.e2e
@pytest.mark.sglang
@pytest.mark.gpu_1
@pytest.mark.model(FAULT_TOLERANCE_MODEL_NAME)
@pytest.mark.xfail(strict=False)
def test_request_cancellation_sglang_aggregated(
    request, runtime_services, predownload_models
):
    """
    End-to-end test for request cancellation functionality in aggregated mode.

    This test verifies that when a request is cancelled by the client,
    the system properly handles the cancellation and cleans up resources
    on the worker side in aggregated (agg) mode.

    TODO: Test is currently flaky/failing due to SGLang limitations with prefill cancellation.
    See: https://github.com/sgl-project/sglang/issues/11139
    """
    logger.info("Sanity check if latest test is getting executed")
    # Step 1: Start the frontend
    with DynamoFrontendProcess(request) as frontend:
        logger.info("Frontend started successfully")

        # Step 2: Start an aggregated worker
        with DynamoWorkerProcess(request, mode="agg") as worker:
            logger.info(f"Aggregated Worker PID: {worker.get_pid()}")
            # TODO: Why wait after worker ready fixes frontend 404 / 500 flakiness?
            time.sleep(2)

            # Step 3: Test request cancellation with polling approach
            frontend_log_offset, worker_log_offset = 0, 0

            test_scenarios = [
                ("completion", "Completion request cancellation"),
                ("chat_completion", "Chat completion request cancellation"),
                (
                    "chat_completion_stream",
                    "Chat completion stream request cancellation",
                ),
            ]

            for request_type, description in test_scenarios:
                logger.info(f"Testing {description.lower()}...")

                # Send the request (non-blocking)
                cancellable_req = send_cancellable_request(request_type)

                # Poll for "New Request ID" pattern (Dynamo context ID)
                request_id, worker_log_offset = poll_for_pattern(
                    process=worker,
                    pattern="New Request ID: ",
                    log_offset=worker_log_offset,
                    match_type="contains",
                )

                # For streaming, read one response first to trigger SGLang ID logging
                if request_type == "chat_completion_stream":
                    read_streaming_responses(cancellable_req, expected_count=1)

                # Wait for SGLang to actually start processing (get SGLang request ID)
                _, worker_log_offset = poll_for_pattern(
                    process=worker,
                    pattern="New SGLang Request ID: ",
                    log_offset=worker_log_offset,
                    match_type="contains",
                )

                # Now we know SGLang has the request, cancel it
                cancellable_req.cancel()
                logger.info(f"Cancelled request ID: {request_id}")

                # Poll for "Aborted Request ID" with matching ID
                _, worker_log_offset = poll_for_pattern(
                    process=worker,
                    pattern=f"Aborted Request ID: {request_id}",
                    log_offset=worker_log_offset,
                    max_wait_ms=2000,
                )

                # Verify frontend log has kill message
                _, frontend_log_offset = poll_for_pattern(
                    process=frontend,
                    pattern="issued control message Kill to sender",
                    log_offset=frontend_log_offset,
                )

                logger.info(f"{description} detected successfully")


@pytest.mark.e2e
@pytest.mark.sglang
@pytest.mark.gpu_2
@pytest.mark.model(FAULT_TOLERANCE_MODEL_NAME)
def test_request_cancellation_sglang_decode_cancel(
    request, runtime_services, predownload_models
):
    """
    End-to-end test for request cancellation during remote decode phase.

    This test verifies that when a request is cancelled by the client during the remote decode phase,
    the system properly handles the cancellation and cleans up resources
    on both the prefill and decode workers in a disaggregated setup.

    Note: This test requires 2 GPUs to run decode and prefill workers on separate GPUs.
    """

    # Step 1: Start the frontend
    with DynamoFrontendProcess(request) as frontend:
        logger.info("Frontend started successfully")

        # Step 2: Start the decode worker
        with DynamoWorkerProcess(request, mode="decode") as decode_worker:
            logger.info(f"Decode Worker PID: {decode_worker.get_pid()}")

            # Step 3: Start the prefill worker
            with DynamoWorkerProcess(request, mode="prefill") as prefill_worker:
                logger.info(f"Prefill Worker PID: {prefill_worker.get_pid()}")

                # TODO: Why wait after worker ready fixes frontend 404 / 500 flakiness?
                time.sleep(2)

                # Step 4: Test request cancellation during remote decode phase
                logger.info(
                    "Testing chat completion stream request cancellation during remote decode phase..."
                )

                # Send streaming request (non-blocking)
                cancellable_req = send_cancellable_request("chat_completion_stream")

                # Poll for "New Request ID" pattern in decode worker (Dynamo context ID)
                request_id, decode_log_offset = poll_for_pattern(
                    process=decode_worker,
                    pattern="New Request ID: ",
                    match_type="contains",
                )

                # Verify same request ID reached prefill worker
                _, prefill_log_offset = poll_for_pattern(
                    process=prefill_worker,
                    pattern=f"New Request ID: {request_id}",
                )

                # Read one response first to trigger SGLang ID logging in decode worker
                read_streaming_responses(cancellable_req, expected_count=1)

                # Wait for SGLang to start processing in decode worker
                _, decode_log_offset = poll_for_pattern(
                    process=decode_worker,
                    pattern="New SGLang Request ID: ",
                    log_offset=decode_log_offset,
                    match_type="contains",
                )

                # Now we know SGLang has the request in decode worker, cancel it
                cancellable_req.cancel()
                logger.info(f"Cancelled request ID: {request_id}")

                # Poll for "Aborted Request ID" in decode worker
                _, decode_log_offset = poll_for_pattern(
                    process=decode_worker,
                    pattern=f"Aborted Request ID: {request_id}",
                    log_offset=decode_log_offset,
                )

                # Verify frontend log has kill message
                _, frontend_log_offset = poll_for_pattern(
                    process=frontend,
                    pattern="issued control message Kill to sender",
                )

                logger.info(
                    "Chat completion stream cancellation in decode phase detected successfully"
                )