Files
nanobot/tests/test_heartbeat_service.py
Xubin Ren 411b059dd2 refactor: replace <SILENT_OK> with structured post-run evaluation
- Add nanobot/utils/evaluator.py: lightweight LLM tool-call to decide notify/silent after background task execution
- Remove magic token injection from heartbeat and cron prompts
- Clean session history (no more <SILENT_OK> pollution)
- Add tests for evaluator and updated heartbeat three-phase flow
2026-03-14 17:41:08 +08:00

253 lines
6.7 KiB
Python

import asyncio
import pytest
from nanobot.heartbeat.service import HeartbeatService
from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
class DummyProvider(LLMProvider):
def __init__(self, responses: list[LLMResponse]):
super().__init__()
self._responses = list(responses)
self.calls = 0
async def chat(self, *args, **kwargs) -> LLMResponse:
self.calls += 1
if self._responses:
return self._responses.pop(0)
return LLMResponse(content="", tool_calls=[])
def get_default_model(self) -> str:
return "test-model"
@pytest.mark.asyncio
async def test_start_is_idempotent(tmp_path) -> None:
provider = DummyProvider([])
service = HeartbeatService(
workspace=tmp_path,
provider=provider,
model="openai/gpt-4o-mini",
interval_s=9999,
enabled=True,
)
await service.start()
first_task = service._task
await service.start()
assert service._task is first_task
service.stop()
await asyncio.sleep(0)
@pytest.mark.asyncio
async def test_decide_returns_skip_when_no_tool_call(tmp_path) -> None:
provider = DummyProvider([LLMResponse(content="no tool call", tool_calls=[])])
service = HeartbeatService(
workspace=tmp_path,
provider=provider,
model="openai/gpt-4o-mini",
)
action, tasks = await service._decide("heartbeat content")
assert action == "skip"
assert tasks == ""
@pytest.mark.asyncio
async def test_trigger_now_executes_when_decision_is_run(tmp_path) -> None:
(tmp_path / "HEARTBEAT.md").write_text("- [ ] do thing", encoding="utf-8")
provider = DummyProvider([
LLMResponse(
content="",
tool_calls=[
ToolCallRequest(
id="hb_1",
name="heartbeat",
arguments={"action": "run", "tasks": "check open tasks"},
)
],
)
])
called_with: list[str] = []
async def _on_execute(tasks: str) -> str:
called_with.append(tasks)
return "done"
service = HeartbeatService(
workspace=tmp_path,
provider=provider,
model="openai/gpt-4o-mini",
on_execute=_on_execute,
)
result = await service.trigger_now()
assert result == "done"
assert called_with == ["check open tasks"]
@pytest.mark.asyncio
async def test_trigger_now_returns_none_when_decision_is_skip(tmp_path) -> None:
(tmp_path / "HEARTBEAT.md").write_text("- [ ] do thing", encoding="utf-8")
provider = DummyProvider([
LLMResponse(
content="",
tool_calls=[
ToolCallRequest(
id="hb_1",
name="heartbeat",
arguments={"action": "skip"},
)
],
)
])
async def _on_execute(tasks: str) -> str:
return tasks
service = HeartbeatService(
workspace=tmp_path,
provider=provider,
model="openai/gpt-4o-mini",
on_execute=_on_execute,
)
assert await service.trigger_now() is None
@pytest.mark.asyncio
async def test_tick_notifies_when_evaluator_says_yes(tmp_path, monkeypatch) -> None:
"""Phase 1 run -> Phase 2 execute -> Phase 3 evaluate=notify -> on_notify called."""
(tmp_path / "HEARTBEAT.md").write_text("- [ ] check deployments", encoding="utf-8")
provider = DummyProvider([
LLMResponse(
content="",
tool_calls=[
ToolCallRequest(
id="hb_1",
name="heartbeat",
arguments={"action": "run", "tasks": "check deployments"},
)
],
),
])
executed: list[str] = []
notified: list[str] = []
async def _on_execute(tasks: str) -> str:
executed.append(tasks)
return "deployment failed on staging"
async def _on_notify(response: str) -> None:
notified.append(response)
service = HeartbeatService(
workspace=tmp_path,
provider=provider,
model="openai/gpt-4o-mini",
on_execute=_on_execute,
on_notify=_on_notify,
)
async def _eval_notify(*a, **kw):
return True
monkeypatch.setattr("nanobot.utils.evaluator.evaluate_response", _eval_notify)
await service._tick()
assert executed == ["check deployments"]
assert notified == ["deployment failed on staging"]
@pytest.mark.asyncio
async def test_tick_suppresses_when_evaluator_says_no(tmp_path, monkeypatch) -> None:
"""Phase 1 run -> Phase 2 execute -> Phase 3 evaluate=silent -> on_notify NOT called."""
(tmp_path / "HEARTBEAT.md").write_text("- [ ] check status", encoding="utf-8")
provider = DummyProvider([
LLMResponse(
content="",
tool_calls=[
ToolCallRequest(
id="hb_1",
name="heartbeat",
arguments={"action": "run", "tasks": "check status"},
)
],
),
])
executed: list[str] = []
notified: list[str] = []
async def _on_execute(tasks: str) -> str:
executed.append(tasks)
return "everything is fine, no issues"
async def _on_notify(response: str) -> None:
notified.append(response)
service = HeartbeatService(
workspace=tmp_path,
provider=provider,
model="openai/gpt-4o-mini",
on_execute=_on_execute,
on_notify=_on_notify,
)
async def _eval_silent(*a, **kw):
return False
monkeypatch.setattr("nanobot.utils.evaluator.evaluate_response", _eval_silent)
await service._tick()
assert executed == ["check status"]
assert notified == []
@pytest.mark.asyncio
async def test_decide_retries_transient_error_then_succeeds(tmp_path, monkeypatch) -> None:
provider = DummyProvider([
LLMResponse(content="429 rate limit", finish_reason="error"),
LLMResponse(
content="",
tool_calls=[
ToolCallRequest(
id="hb_1",
name="heartbeat",
arguments={"action": "run", "tasks": "check open tasks"},
)
],
),
])
delays: list[int] = []
async def _fake_sleep(delay: int) -> None:
delays.append(delay)
monkeypatch.setattr(asyncio, "sleep", _fake_sleep)
service = HeartbeatService(
workspace=tmp_path,
provider=provider,
model="openai/gpt-4o-mini",
)
action, tasks = await service._decide("heartbeat content")
assert action == "run"
assert tasks == "check open tasks"
assert provider.calls == 2
assert delays == [1]