[测试、性能、安全、验收与归档]：完成全量测试验收与 OpenSpec 归档，包含 CLI 验收、NewAPI smoke、安全扫描和主 spec 更新

tests/test_pipeline_llm_tts.py

@@ -120,12 +120,14 @@ class PipelineLlmTtsTests(unittest.TestCase):
             def __exit__(self, *args: object) -> None:
                 return None
 
-            def __iter__(self):
+            def read(self):
                 event = {"choices": [{"delta": {"content": "你好。"}, "finish_reason": None}]}
                 done = {"choices": [{"delta": {}, "finish_reason": "stop"}]}
-                yield f"data: {json.dumps(event, ensure_ascii=False)}\n".encode()
-                yield f"data: {json.dumps(done, ensure_ascii=False)}\n".encode()
-                yield b"data: [DONE]\n"
+                return (
+                    f"data: {json.dumps(event, ensure_ascii=False)}\n"
+                    f"data: {json.dumps(done, ensure_ascii=False)}\n"
+                    "data: [DONE]\n"
+                ).encode()
 
         requests = []
 
@@ -146,6 +148,27 @@ class PipelineLlmTtsTests(unittest.TestCase):
         self.assertTrue(body["stream"])
         self.assertEqual(body["model"], "test-model")
 
+    def test_openai_non_stream_json_parser(self) -> None:
+        class FakeResponse:
+            def __enter__(self) -> "FakeResponse":
+                return self
+
+            def __exit__(self, *args: object) -> None:
+                return None
+
+            def read(self):
+                return json.dumps({"choices": [{"message": {"content": "非流式回复。"}}]}).encode()
+
+        config = AppConfig(
+            llm_base_url="https://newapi.mkbk.shop",
+            llm_api_key="secret",
+            llm_model="test-model",
+            llm_api_style="chat_completions",
+            llm_stream=False,
+        )
+        provider = OpenAICompatibleLlmProvider(config, urlopen=lambda request, timeout: FakeResponse())
+        self.assertEqual(list(provider.stream_reply([Message("user", "你好", 1.0)]))[0].text_delta, "非流式回复。")
+
 
 if __name__ == "__main__":
     unittest.main()