64 lines
2.2 KiB
Python
64 lines
2.2 KiB
Python
import unittest
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import requests
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from sglang.srt.utils import kill_child_process
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from sglang.test.test_utils import (
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DEFAULT_SMALL_MODEL_NAME_FOR_TEST,
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DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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DEFAULT_URL_FOR_TEST,
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popen_launch_server,
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)
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class TestEnableMetrics(unittest.TestCase):
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def test_metrics_enabled(self):
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"""Test that metrics endpoint returns data when enabled"""
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process = popen_launch_server(
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DEFAULT_SMALL_MODEL_NAME_FOR_TEST,
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DEFAULT_URL_FOR_TEST,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=["--enable-metrics"],
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)
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try:
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# Make a request to generate some metrics
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response = requests.get(f"{DEFAULT_URL_FOR_TEST}/health_generate")
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self.assertEqual(response.status_code, 200)
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# Get metrics
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metrics_response = requests.get(f"{DEFAULT_URL_FOR_TEST}/metrics")
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self.assertEqual(metrics_response.status_code, 200)
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metrics_content = metrics_response.text
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print(f"{metrics_content=}")
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# Verify essential metrics are present
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essential_metrics = [
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"sglang:prompt_tokens_total",
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"sglang:generation_tokens_total",
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"sglang:max_total_num_tokens",
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"sglang:context_len",
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"sglang:time_to_first_token_seconds",
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"sglang:time_per_output_token_seconds",
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"sglang:e2e_request_latency_seconds",
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]
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for metric in essential_metrics:
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self.assertIn(metric, metrics_content, f"Missing metric: {metric}")
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# Verify model name label is present and correct
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expected_model_name = DEFAULT_SMALL_MODEL_NAME_FOR_TEST
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self.assertIn(f'model_name="{expected_model_name}"', metrics_content)
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# Verify metrics have values (not empty)
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self.assertIn("_sum{", metrics_content)
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self.assertIn("_count{", metrics_content)
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self.assertIn("_bucket{", metrics_content)
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finally:
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kill_child_process(process.pid, include_self=True)
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if __name__ == "__main__":
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unittest.main()
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