hermes-agent/tests/run_agent/test_background_review.py
teknium1 8c6b0c9ecd test(memory): cover cache-parity + runtime whitelist on background review fork
- test_background_review_does_not_narrow_toolset_schema: review fork must
  NOT pass enabled_toolsets to AIAgent (full parent schema = matching
  Anthropic cache key on the 'tools' field).
- test_background_review_installs_thread_local_whitelist: the runtime
  whitelist that replaces schema-level narrowing must contain memory +
  skills tools and exclude terminal / send_message / delegate_task /
  web_search / execute_code.
- test_review_fork_inherits_parent_cached_system_prompt: new test for
  PR #17276's first root cause — the fork's _cached_system_prompt must
  equal the parent's byte-for-byte.
- test_review_fork_pins_session_start_and_session_id: defensive belt-and-
  suspenders for the cached-prompt inheritance.

Inverted the original test_background_review_agent_uses_restricted_toolsets
(which asserted the schema-level narrowing) — that narrowing was the
direct cause of #25322's cache miss, and the runtime whitelist replaces
its safety claim without breaking cache parity.

Refs #25322, #15204, PR #17276.
2026-05-13 22:12:47 -07:00

195 lines
6.3 KiB
Python

"""Regression tests for background review agent cleanup."""
from __future__ import annotations
import run_agent as run_agent_module
from run_agent import AIAgent
def _bare_agent() -> AIAgent:
agent = object.__new__(AIAgent)
agent.model = "fake-model"
agent.platform = "telegram"
agent.provider = "openai"
agent.base_url = ""
agent.api_key = ""
agent.api_mode = ""
agent.session_id = "test-session"
agent._parent_session_id = ""
agent._credential_pool = None
agent._memory_store = object()
agent._memory_enabled = True
agent._user_profile_enabled = False
agent._cached_system_prompt = "test-cached-system-prompt"
import datetime as _dt
agent.session_start = _dt.datetime(2026, 1, 1, 12, 0, 0)
agent._MEMORY_REVIEW_PROMPT = "review memory"
agent._SKILL_REVIEW_PROMPT = "review skills"
agent._COMBINED_REVIEW_PROMPT = "review both"
agent.background_review_callback = None
agent.status_callback = None
agent._safe_print = lambda *_args, **_kwargs: None
return agent
class ImmediateThread:
def __init__(self, *, target, daemon=None, name=None):
self._target = target
def start(self):
self._target()
def test_background_review_shuts_down_memory_provider_before_close(monkeypatch):
events = []
class FakeReviewAgent:
def __init__(self, **kwargs):
events.append(("init", kwargs))
self._session_messages = []
def run_conversation(self, **kwargs):
events.append(("run_conversation", kwargs))
def shutdown_memory_provider(self):
events.append(("shutdown_memory_provider", None))
def close(self):
events.append(("close", None))
monkeypatch.setattr(run_agent_module, "AIAgent", FakeReviewAgent)
monkeypatch.setattr(run_agent_module.threading, "Thread", ImmediateThread)
agent = _bare_agent()
AIAgent._spawn_background_review(
agent,
messages_snapshot=[{"role": "user", "content": "hello"}],
review_memory=True,
)
assert [name for name, _payload in events] == [
"init",
"run_conversation",
"shutdown_memory_provider",
"close",
]
def test_background_review_installs_auto_deny_approval_callback(monkeypatch):
"""Regression guard for #15216.
The background review thread must install a non-interactive approval
callback. If it doesn't, any dangerous-command guard the review agent
trips falls back to input() on a daemon thread, which deadlocks against
the parent's prompt_toolkit TUI.
"""
import tools.terminal_tool as tt
observed: dict = {"during_run": "<unread>", "after_finally": "<unread>"}
class FakeReviewAgent:
def __init__(self, **kwargs):
self._session_messages = []
def run_conversation(self, **kwargs):
# Capture what the callback looks like mid-run. It must be
# a callable (the auto-deny) -- not None.
observed["during_run"] = tt._get_approval_callback()
def shutdown_memory_provider(self):
pass
def close(self):
pass
monkeypatch.setattr(run_agent_module, "AIAgent", FakeReviewAgent)
monkeypatch.setattr(run_agent_module.threading, "Thread", ImmediateThread)
# Start from a clean slot.
tt.set_approval_callback(None)
agent = _bare_agent()
AIAgent._spawn_background_review(
agent,
messages_snapshot=[{"role": "user", "content": "hello"}],
review_memory=True,
)
observed["after_finally"] = tt._get_approval_callback()
assert callable(observed["during_run"]), (
"Background review did not install an approval callback on its "
"worker thread; dangerous-command prompts will deadlock against "
"the parent TUI (#15216)."
)
# The installed callback must deny (it's a safety gate, not a prompt).
assert observed["during_run"]("rm -rf /", "test") == "deny"
assert observed["after_finally"] is None, (
"Background review leaked its approval callback into the worker "
"thread's TLS slot; a recycled thread-id could reuse it."
)
def test_background_review_summary_is_attributed_to_self_improvement_loop(monkeypatch):
"""The CLI/gateway emission must identify the self-improvement loop.
Users who miss the line in their terminal have no way to tell that the
background review was what modified their skill/memory stores. The
summary prefix ``💾 Self-improvement review: …`` makes the origin
explicit so both the CLI and gateway deliveries are unambiguous.
"""
import json
captured_prints: list = []
captured_bg_callback: list = []
class FakeReviewAgent:
def __init__(self, **kwargs):
# Simulate a review that successfully updated memory so
# _summarize_background_review_actions returns a real action.
self._session_messages = [
{
"role": "tool",
"tool_call_id": "call_bg",
"content": json.dumps(
{"success": True, "message": "Entry added", "target": "memory"}
),
}
]
def run_conversation(self, **kwargs):
pass
def shutdown_memory_provider(self):
pass
def close(self):
pass
monkeypatch.setattr(run_agent_module, "AIAgent", FakeReviewAgent)
monkeypatch.setattr(run_agent_module.threading, "Thread", ImmediateThread)
agent = _bare_agent()
agent._safe_print = lambda *a, **kw: captured_prints.append(" ".join(str(x) for x in a))
agent.background_review_callback = lambda msg: captured_bg_callback.append(msg)
AIAgent._spawn_background_review(
agent,
messages_snapshot=[{"role": "user", "content": "hi"}],
review_memory=True,
)
# Exactly one summary should have been emitted, and it must identify
# the self-improvement review explicitly.
assert len(captured_prints) == 1, captured_prints
printed = captured_prints[0]
assert "Self-improvement review" in printed, printed
assert "Memory updated" in printed, printed
# Gateway path gets the same prefix.
assert len(captured_bg_callback) == 1
assert captured_bg_callback[0].startswith("💾 Self-improvement review:"), (
captured_bg_callback[0]
)