Test the case when max_new_tokens is very large (#1038)

test/srt/run_suite.py

@@ -5,13 +5,15 @@ from sglang.test.test_utils import run_unittest_files
 
 suites = {
     "minimal": [
-        "test_eval_accuracy.py",
-        "test_openai_server.py",
-        "test_vision_openai_server.py",
-        "test_embedding_openai_server.py",
         "test_chunked_prefill.py",
+        "test_embedding_openai_server.py",
+        "test_eval_accuracy.py",
+        "test_large_max_new_tokens.py",
+        "test_openai_server.py",
+        "test_skip_tokenizer_init.py",
         "test_torch_compile.py",
-        "test_models_from_modelscope.py",
+        "test_vision_openai_server.py",
+        "test_large_max_new_tokens.py",
         "models/test_generation_models.py",
         "models/test_embedding_models.py",
         "sampling/penaltylib",

test/srt/test_large_max_new_tokens.py

@@ -0,0 +1,72 @@
+import json
+import os
+import time
+import unittest
+from concurrent.futures import ThreadPoolExecutor
+
+import openai
+
+from sglang.srt.hf_transformers_utils import get_tokenizer
+from sglang.srt.utils import kill_child_process
+from sglang.test.test_utils import DEFAULT_MODEL_NAME_FOR_TEST, popen_launch_server
+
+
+class TestOpenAIServer(unittest.TestCase):
+
+    @classmethod
+    def setUpClass(cls):
+        cls.model = DEFAULT_MODEL_NAME_FOR_TEST
+        cls.base_url = "http://127.0.0.1:8157"
+        cls.api_key = "sk-123456"
+        cls.process = popen_launch_server(
+            cls.model,
+            cls.base_url,
+            timeout=300,
+            api_key=cls.api_key,
+            other_args=("--max-total-token", "1024"),
+            env={"SGLANG_CLIP_MAX_NEW_TOKENS": "256", **os.environ},
+            return_stdout_stderr=True,
+        )
+        cls.base_url += "/v1"
+        cls.tokenizer = get_tokenizer(DEFAULT_MODEL_NAME_FOR_TEST)
+
+    @classmethod
+    def tearDownClass(cls):
+        kill_child_process(cls.process.pid)
+
+    def run_chat_completion(self):
+        client = openai.Client(api_key=self.api_key, base_url=self.base_url)
+        response = client.chat.completions.create(
+            model=self.model,
+            messages=[
+                {"role": "system", "content": "You are a helpful AI assistant"},
+                {
+                    "role": "user",
+                    "content": "Please repeat the world 'hello' for 10000 times.",
+                },
+            ],
+            temperature=0,
+        )
+        return response
+
+    def test_chat_completion(self):
+        num_requests = 4
+
+        futures = []
+        with ThreadPoolExecutor(16) as executor:
+            for i in range(num_requests):
+                futures.append(executor.submit(self.run_chat_completion))
+
+            all_requests_running = False
+            for line in iter(self.process.stderr.readline, ""):
+                line = str(line)
+                print(line, end="")
+                if f"#running-req: {num_requests}" in line:
+                    all_requests_running = True
+                    break
+
+        assert all_requests_running
+
+
+if __name__ == "__main__":
+    unittest.main()