fix: use integer dtype for random_seed in query script

scripts/deploy/nlp/query.py

@@ -114,7 +114,7 @@ def query_llm(
         inputs["temperature"] = np.full(prompts.shape, temperature, dtype=np.single)
 
     if random_seed is not None:
-        inputs["random_seed"] = np.full(prompts.shape, random_seed, dtype=np.single)
+        inputs["random_seed"] = np.full(prompts.shape, random_seed, dtype=np.int_)
 
     if stop_words_list is not None:
         stop_words_list = np.char.encode(stop_words_list, "utf-8")

tests/unit_tests/deploy/test_query_script.py

@@ -0,0 +1,54 @@
+# Copyright (c) 2026, NVIDIA CORPORATION.  All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from unittest.mock import MagicMock, patch
+
+import numpy as np
+import pytest
+
+
+@pytest.fixture
+def query_llm_module():
+    """Import query.py with pytriton clients mocked."""
+    with patch.dict(
+        "sys.modules",
+        {
+            "pytriton": MagicMock(),
+            "pytriton.client": MagicMock(),
+        },
+    ):
+        from scripts.deploy.nlp import query as query_module
+
+        yield query_module
+
+
+class TestQueryLLMInputs:
+    @patch("scripts.deploy.nlp.query.ModelClient")
+    def test_random_seed_uses_int_dtype(self, mock_client, query_llm_module):
+        """random_seed must be passed as an integer array, not float."""
+        mock_instance = MagicMock()
+        mock_client.return_value.__enter__.return_value = mock_instance
+        mock_instance.infer_batch.return_value = {"outputs": np.array([b"response"])}
+        mock_instance.model_config.outputs = [MagicMock(dtype=np.bytes_)]
+
+        query_llm_module.query_llm(
+            url="localhost:8000",
+            model_name="test",
+            prompts=["hello"],
+            random_seed=42,
+        )
+
+        call_kwargs = mock_instance.infer_batch.call_args.kwargs
+        assert call_kwargs["random_seed"].dtype == np.int_
+        assert call_kwargs["random_seed"][0] == 42