refactor(tests): optimize unit test structure

tests/agent/test_evaluator.py

@@ -0,0 +1,63 @@
+import pytest
+
+from nanobot.utils.evaluator import evaluate_response
+from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
+
+
+class DummyProvider(LLMProvider):
+    def __init__(self, responses: list[LLMResponse]):
+        super().__init__()
+        self._responses = list(responses)
+
+    async def chat(self, *args, **kwargs) -> LLMResponse:
+        if self._responses:
+            return self._responses.pop(0)
+        return LLMResponse(content="", tool_calls=[])
+
+    def get_default_model(self) -> str:
+        return "test-model"
+
+
+def _eval_tool_call(should_notify: bool, reason: str = "") -> LLMResponse:
+    return LLMResponse(
+        content="",
+        tool_calls=[
+            ToolCallRequest(
+                id="eval_1",
+                name="evaluate_notification",
+                arguments={"should_notify": should_notify, "reason": reason},
+            )
+        ],
+    )
+
+
+@pytest.mark.asyncio
+async def test_should_notify_true() -> None:
+    provider = DummyProvider([_eval_tool_call(True, "user asked to be reminded")])
+    result = await evaluate_response("Task completed with results", "check emails", provider, "m")
+    assert result is True
+
+
+@pytest.mark.asyncio
+async def test_should_notify_false() -> None:
+    provider = DummyProvider([_eval_tool_call(False, "routine check, nothing new")])
+    result = await evaluate_response("All clear, no updates", "check status", provider, "m")
+    assert result is False
+
+
+@pytest.mark.asyncio
+async def test_fallback_on_error() -> None:
+    class FailingProvider(DummyProvider):
+        async def chat(self, *args, **kwargs) -> LLMResponse:
+            raise RuntimeError("provider down")
+
+    provider = FailingProvider([])
+    result = await evaluate_response("some response", "some task", provider, "m")
+    assert result is True
+
+
+@pytest.mark.asyncio
+async def test_no_tool_call_fallback() -> None:
+    provider = DummyProvider([LLMResponse(content="I think you should notify", tool_calls=[])])
+    result = await evaluate_response("some response", "some task", provider, "m")
+    assert result is True