[连续对话判断]：完成自动持续对话和播报打断，包含回复意图判断、免唤醒追问和打断回归测试

tests/test_continuation.py

@@ -0,0 +1,81 @@
+from __future__ import annotations
+
+import unittest
+
+from owner_voice_pet.continuation import (
+    HybridContinuationDecisionProvider,
+    LlmContinuationDecisionProvider,
+    RuleContinuationDecisionProvider,
+)
+from owner_voice_pet.models import Message, ReplyDelta
+
+
+class FakeClassifierLlm:
+    def __init__(self, text: str) -> None:
+        self.text = text
+        self.calls: list[list[Message]] = []
+
+    def stream_reply(self, messages):
+        self.calls.append(list(messages))
+        yield ReplyDelta(self.text, finish_reason="stop")
+
+
+class ContinuationDecisionTests(unittest.TestCase):
+    def test_rule_continue_for_assistant_question(self) -> None:
+        decision = RuleContinuationDecisionProvider().decide(
+            user_text="讲讲天气",
+            assistant_text="你想继续听哪一部分？",
+            history=[],
+        )
+
+        self.assertEqual(decision.action, "continue")
+        self.assertGreaterEqual(decision.confidence, 0.65)
+
+    def test_rule_standby_for_completed_answer(self) -> None:
+        decision = RuleContinuationDecisionProvider().decide(
+            user_text="今天天气怎么样",
+            assistant_text="这是今天的天气。",
+            history=[],
+        )
+
+        self.assertEqual(decision.action, "standby")
+        self.assertGreaterEqual(decision.confidence, 0.65)
+
+    def test_hybrid_low_confidence_llm_defaults_to_standby(self) -> None:
+        llm = FakeClassifierLlm('{"action":"continue","confidence":0.3,"reason":"弱"}')
+        provider = HybridContinuationDecisionProvider(
+            RuleContinuationDecisionProvider(),
+            LlmContinuationDecisionProvider(llm, threshold=0.65),
+            threshold=0.65,
+        )
+
+        decision = provider.decide(
+            user_text="继续",
+            assistant_text="我还可以从背景原因和下一步影响两个方向继续展开",
+            history=[],
+        )
+
+        self.assertEqual(decision.action, "standby")
+        self.assertEqual(len(llm.calls), 1)
+
+    def test_hybrid_high_confidence_llm_can_continue(self) -> None:
+        llm = FakeClassifierLlm('{"action":"continue","confidence":0.91,"reason":"等待用户选择"}')
+        provider = HybridContinuationDecisionProvider(
+            RuleContinuationDecisionProvider(),
+            LlmContinuationDecisionProvider(llm, threshold=0.65),
+            threshold=0.65,
+        )
+
+        decision = provider.decide(
+            user_text="继续",
+            assistant_text="我还可以从背景原因和下一步影响两个方向继续展开",
+            history=[],
+        )
+
+        self.assertEqual(decision.action, "continue")
+        self.assertEqual(decision.provider, "hybrid")
+        self.assertEqual(len(llm.calls), 1)
+
+
+if __name__ == "__main__":
+    unittest.main()