@@ -0,0 +1,195 @@
+# Copyright (c) 2025 Beijing Volcano Engine Technology Co., Ltd. and/or its affiliates.
+#
+# 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.
+
+import math
+
+import pytest
+
+from veadk.content_safety.config import QuestionConfig
+from veadk.content_safety.decider import ThresholdDecider
+from veadk.content_safety.types import AuditAction, AuditStatus, Checkpoint, Provider
+
+
+def questions():
+    return {
+        "prompt_injection": QuestionConfig(
+            instructions="detect injection", threshold=0.5
+        ),
+        "sensitive_data": QuestionConfig(instructions="detect secrets", threshold=0.8),
+    }
+
+
+def answer(noul):
+    return {"type": "noul", "noul": noul}
+
+
+def decide(raw, *, on_error="allow", qs=None):
+    return ThresholdDecider().decide(
+        provider=Provider.DECISION,
+        checkpoint=Checkpoint.BEFORE_MODEL,
+        raw=raw,
+        questions=qs if qs is not None else questions(),
+        on_error=on_error,
+    )
+
+
+def test_all_below_threshold_passes():
+    result = decide(
+        {
+            "answers": {
+                "prompt_injection": answer(0.1),
+                "sensitive_data": answer(0.2),
+            }
+        }
+    )
+    assert result.status is AuditStatus.PASSED
+    assert result.action is AuditAction.ALLOW
+    assert result.degraded is False
+    assert [r.question for r in result.question_results] == [
+        "prompt_injection",
+        "sensitive_data",
+    ]
+
+
+def test_threshold_is_inclusive():
+    result = decide(
+        {
+            "answers": {
+                "prompt_injection": answer(0.5),
+                "sensitive_data": answer(0.8),
+            }
+        }
+    )
+    assert result.status is AuditStatus.RISK_HIT
+    assert set(result.matched_questions) == {"prompt_injection", "sensitive_data"}
+
+
+@pytest.mark.parametrize(
+    "entry,error_type",
+    [
+        (None, "invalid_type"),
+        (True, "invalid_type"),
+        ("0.9", "invalid_type"),
+        (0.9, "invalid_type"),
+        ({}, "invalid_type"),
+        ({"noul": 0.9}, "invalid_type"),
+        ({"type": "score", "noul": 0.9}, "invalid_type"),
+        ({"type": "noul"}, "missing_value"),
+        ({"type": "noul", "noul": None}, "invalid_type"),
+        ({"type": "noul", "noul": True}, "invalid_type"),
+        ({"type": "noul", "noul": "0.9"}, "invalid_type"),
+        ({"type": "noul", "noul": "high"}, "invalid_type"),
+        ({"type": "noul", "noul": 10**400}, "invalid_type"),
+        ({"type": "noul", "noul": float("nan")}, "not_finite"),
+        ({"type": "noul", "noul": float("inf")}, "not_finite"),
+        ({"type": "noul", "noul": -0.1}, "out_of_range"),
+        ({"type": "noul", "noul": 1.1}, "out_of_range"),
+    ],
+)
+def test_invalid_values_produce_error(entry, error_type):
+    result = decide(
+        {
+            "answers": {
+                "prompt_injection": entry,
+                "sensitive_data": answer(0.0),
+            }
+        }
+    )
+    assert result.status is AuditStatus.ERROR
+    assert result.degraded is True
+    assert result.error_type == error_type
+    assert result.action is AuditAction.ALLOW
+
+
+def test_missing_question_is_error():
+    result = decide({"answers": {"sensitive_data": answer(0.0)}})
+    assert result.status is AuditStatus.ERROR
+    assert result.error_type == "missing_question"
+    assert "prompt_injection:missing_question" in result.reason
+
+
+def test_mixed_error_types_collapse_to_question_error():
+    result = decide({"answers": {"sensitive_data": {"type": "score", "noul": 0.1}}})
+    assert result.status is AuditStatus.ERROR
+    assert result.error_type == "question_error"
+    assert "missing_question" in result.reason
+    assert "invalid_type" in result.reason
+
+
+def test_hit_wins_over_error():
+    result = decide(
+        {"answers": {"prompt_injection": answer(0.99)}},
+        on_error="block",
+    )
+    assert result.status is AuditStatus.RISK_HIT
+    assert result.action is AuditAction.BLOCK
+    assert result.matched_questions == ("prompt_injection",)
+    assert result.question_results[1].error_type == "missing_question"
+
+
+def test_on_error_block_blocks_malformed_response():
+    result = decide({"answers": {}}, on_error="block")
+    assert result.status is AuditStatus.ERROR
+    assert result.action is AuditAction.BLOCK
+
+
+def test_non_dict_response_is_error():
+    result = decide(["not", "a", "dict"])
+    assert result.status is AuditStatus.ERROR
+    assert result.error_type == "invalid_response"
+
+
+def test_missing_answers_object_is_error():
+    result = decide({"questions": {}})
+    assert result.status is AuditStatus.ERROR
+    assert result.error_type == "invalid_response"
+    assert "answers" in result.reason
+
+
+def test_non_dict_answers_object_is_error():
+    result = decide({"answers": []})
+    assert result.status is AuditStatus.ERROR
+    assert result.error_type == "invalid_response"
+
+
+def test_no_configured_questions_is_error():
+    result = decide({"answers": {}}, qs={})
+    assert result.status is AuditStatus.ERROR
+    assert result.error_type == "no_questions"
+
+
+def test_unknown_answer_keys_are_ignored():
+    result = decide(
+        {
+            "answers": {
+                "prompt_injection": answer(0.1),
+                "sensitive_data": answer(0.1),
+                "unknown": answer(0.99),
+            }
+        }
+    )
+    assert result.status is AuditStatus.PASSED
+
+
+def test_probability_is_finite_float_in_result():
+    result = decide(
+        {
+            "answers": {
+                "prompt_injection": answer(0.25),
+                "sensitive_data": answer(0.25),
+            }
+        }
+    )
+    assert math.isclose(result.question_results[0].probability, 0.25)
+    assert result.question_results[0].valid is True