"""Tests for /stop preserving partial context from interrupted turns. When /stop cancels an active task, the runtime checkpoint (tool results, assistant messages accumulated so far) should be materialized into session history rather than silently discarded. See: https://github.com/HKUDS/nanobot/issues/2966 """ from __future__ import annotations import asyncio from pathlib import Path from types import SimpleNamespace from typing import Any from unittest.mock import MagicMock, patch, AsyncMock import pytest from nanobot.agent.loop import AgentLoop from nanobot.bus.queue import MessageBus from nanobot.providers.base import LLMProvider def _make_provider(): """Create an LLM provider mock with required attributes.""" from types import SimpleNamespace provider = MagicMock() provider.get_default_model.return_value = "test-model" provider.generation = SimpleNamespace(max_tokens=4096, temperature=0.1, reasoning_effort=None) provider.estimate_prompt_tokens.return_value = (10_000, "test") return provider def _make_loop(tmp_path: Path) -> AgentLoop: """Create a real AgentLoop with mocked provider — avoids patching __init__.""" bus = MessageBus() provider = _make_provider() with patch("nanobot.agent.loop.ContextBuilder"), \ patch("nanobot.agent.loop.SessionManager"), \ patch("nanobot.agent.loop.SubagentManager") as MockSubMgr: MockSubMgr.return_value.cancel_by_session = AsyncMock(return_value=0) return AgentLoop(bus=bus, provider=provider, workspace=tmp_path) class TestStopPreservesContext: """Verify that /stop restores partial context via checkpoint.""" def test_restore_checkpoint_method_exists(self, tmp_path): """AgentLoop should have _restore_runtime_checkpoint.""" loop = _make_loop(tmp_path) assert hasattr(loop, "_restore_runtime_checkpoint") def test_checkpoint_key_constant(self, tmp_path): """The runtime checkpoint key should be defined.""" loop = _make_loop(tmp_path) assert loop._RUNTIME_CHECKPOINT_KEY == "runtime_checkpoint" def test_cancel_dispatch_restores_checkpoint(self, tmp_path): """When a task is cancelled, the checkpoint should be restored.""" loop = _make_loop(tmp_path) session = MagicMock() session.metadata = { "runtime_checkpoint": { "phase": "awaiting_tools", "iteration": 0, "assistant_message": { "role": "assistant", "content": "Let me search for that.", "tool_calls": [{"id": "tc_1", "type": "function", "function": {"name": "web_search", "arguments": "{}"}}], }, "completed_tool_results": [ {"role": "tool", "tool_call_id": "tc_1", "content": "Search results: ..."}, ], "pending_tool_calls": [], } } session.messages = [ {"role": "user", "content": "Search for something"}, ] loop.sessions.get_or_create.return_value = session restored = loop._restore_runtime_checkpoint(session) assert restored is True assert len(session.messages) > 1 assert "runtime_checkpoint" not in session.metadata @pytest.mark.asyncio async def test_dispatch_cancellation_restores_checkpoint(): """Regression for #2966: /stop interrupting _dispatch must materialize the in-flight runtime checkpoint into session.messages before the cancellation unwinds, so the next turn can see the partial work. This exercises the real _dispatch path (locks, pending queues, the CancelledError handler) rather than poking _restore_runtime_checkpoint in isolation, so a future refactor that drops the cancel-time restore is caught by CI instead of silently regressing. """ from nanobot.bus.events import InboundMessage from nanobot.bus.queue import MessageBus bus = MessageBus() provider = MagicMock() provider.get_default_model.return_value = "test-model" workspace = MagicMock() workspace.__truediv__ = MagicMock(return_value=MagicMock()) with patch("nanobot.agent.loop.ContextBuilder"), \ patch("nanobot.agent.loop.SessionManager"), \ patch("nanobot.agent.loop.SubagentManager") as MockSubMgr: MockSubMgr.return_value.cancel_by_session = AsyncMock(return_value=0) loop = AgentLoop(bus=bus, provider=provider, workspace=workspace) checkpoint_key = loop._RUNTIME_CHECKPOINT_KEY session = SimpleNamespace( key="test:c1", metadata={ checkpoint_key: { "phase": "awaiting_tools", "iteration": 0, "assistant_message": { "role": "assistant", "content": "Let me search.", "tool_calls": [ { "id": "tc_1", "type": "function", "function": {"name": "web_search", "arguments": "{}"}, } ], }, "completed_tool_results": [ {"role": "tool", "tool_call_id": "tc_1", "content": "Search hit."}, ], "pending_tool_calls": [], } }, messages=[{"role": "user", "content": "Search for something"}], ) loop.sessions.get_or_create = MagicMock(return_value=session) loop.sessions.save = MagicMock() async def _cancel(*_args, **_kwargs): raise asyncio.CancelledError() loop._process_message = _cancel msg = InboundMessage(channel="test", sender_id="u1", chat_id="c1", content="work") with pytest.raises(asyncio.CancelledError): await loop._dispatch(msg) roles = [m.get("role") for m in session.messages] assert roles == ["user", "assistant", "tool"], ( "Expected the assistant message and completed tool result from the " f"interrupted turn to be materialized into session.messages; got {roles}" ) assert checkpoint_key not in session.metadata, \ "Checkpoint metadata should be cleared after restore" assert loop.sessions.save.called, \ "Session should be persisted so the restored state survives process restart"