fix(agent): prevent runner from exiting while sustained goal is active

`long_task` registers a sustained objective, but `AgentRunner` would still exit with `stop_reason="completed"` when the LLM produced a final text response without calling `complete_goal`. This defeated the purpose of sustained goals. Add `goal_active_predicate` and `goal_continue_message` to `AgentRunSpec`. When the predicate returns `True` at the natural completion checkpoint, inject a continuation message via the existing `_try_drain_injections` machinery, forcing the runner to continue looping. Also extract the default continuation prompt to `nanobot/utils/runtime.py` alongside the existing recovery-message builders.
2026-05-26 00:53:38 +08:00
parent 418cb23da2
commit 7bbd9c7103
4 changed files with 221 additions and 2 deletions
@@ -0,0 +1,184 @@
+"""Tests for sustained-goal continuation in AgentRunner.
+
+When a goal_active_predicate returns True, the runner must not exit with
+stop_reason="completed" after a plain-text final response. Instead it should
+inject a continuation message and keep looping (similar to mid-turn injection).
+"""
+
+from __future__ import annotations
+
+from unittest.mock import AsyncMock, MagicMock
+
+import pytest
+
+from nanobot.config.schema import AgentDefaults
+from nanobot.providers.base import LLMProvider, LLMResponse
+
+_MAX_TOOL_RESULT_CHARS = AgentDefaults().max_tool_result_chars
+
+
+@pytest.mark.asyncio
+async def test_runner_exits_normally_without_predicate():
+    """Baseline: no predicate, runner exits with completed on final text."""
+    from nanobot.agent.runner import AgentRunner, AgentRunSpec
+
+    provider = MagicMock(spec=LLMProvider)
+    provider.chat_with_retry = AsyncMock(return_value=LLMResponse(
+        content="all done", tool_calls=[], usage={},
+    ))
+    tools = MagicMock()
+    tools.get_definitions.return_value = []
+
+    runner = AgentRunner(provider)
+    result = await runner.run(AgentRunSpec(
+        initial_messages=[{"role": "user", "content": "do task"}],
+        tools=tools,
+        model="test-model",
+        max_iterations=2,
+        max_tool_result_chars=_MAX_TOOL_RESULT_CHARS,
+    ))
+
+    assert result.stop_reason == "completed"
+    assert result.final_content == "all done"
+
+
+@pytest.mark.asyncio
+async def test_runner_exits_normally_with_inactive_goal():
+    """Predicate returns False, runner should exit normally."""
+    from nanobot.agent.runner import AgentRunner, AgentRunSpec
+
+    provider = MagicMock(spec=LLMProvider)
+    provider.chat_with_retry = AsyncMock(return_value=LLMResponse(
+        content="all done", tool_calls=[], usage={},
+    ))
+    tools = MagicMock()
+    tools.get_definitions.return_value = []
+
+    runner = AgentRunner(provider)
+    result = await runner.run(AgentRunSpec(
+        initial_messages=[{"role": "user", "content": "do task"}],
+        tools=tools,
+        model="test-model",
+        max_iterations=2,
+        max_tool_result_chars=_MAX_TOOL_RESULT_CHARS,
+        goal_active_predicate=lambda: False,
+    ))
+
+    assert result.stop_reason == "completed"
+    assert result.final_content == "all done"
+
+
+@pytest.mark.asyncio
+async def test_runner_forces_continue_when_goal_active():
+    """Predicate returns True on final text → runner injects continuation and loops.
+
+    We set max_iterations=3 and let the provider return final text every time.
+    Without the fix this would exit on the first iteration with stop_reason
+    "completed". With the fix the runner is forced to continue until
+    max_iterations is hit.
+    """
+    from nanobot.agent.runner import AgentRunner, AgentRunSpec
+
+    provider = MagicMock(spec=LLMProvider)
+    provider.chat_with_retry = AsyncMock(return_value=LLMResponse(
+        content="still working", tool_calls=[], usage={},
+    ))
+    tools = MagicMock()
+    tools.get_definitions.return_value = []
+
+    runner = AgentRunner(provider)
+    result = await runner.run(AgentRunSpec(
+        initial_messages=[{"role": "user", "content": "do task"}],
+        tools=tools,
+        model="test-model",
+        max_iterations=3,
+        max_tool_result_chars=_MAX_TOOL_RESULT_CHARS,
+        goal_active_predicate=lambda: True,
+    ))
+
+    # Because the predicate keeps returning True, the runner should never
+    # naturally complete. It loops until max_iterations is exhausted.
+    assert result.stop_reason == "max_iterations"
+    # The injected continuation message should be present in the message list.
+    user_msgs = [m for m in result.messages if m.get("role") == "user"]
+    assert any("active sustained goal" in str(m.get("content", "")) for m in user_msgs)
+
+
+@pytest.mark.asyncio
+async def test_runner_respects_max_iterations_even_with_active_goal():
+    """A single iteration with active goal still hits max_iterations."""
+    from nanobot.agent.runner import AgentRunner, AgentRunSpec
+
+    provider = MagicMock(spec=LLMProvider)
+    provider.chat_with_retry = AsyncMock(return_value=LLMResponse(
+        content="still working", tool_calls=[], usage={},
+    ))
+    tools = MagicMock()
+    tools.get_definitions.return_value = []
+
+    runner = AgentRunner(provider)
+    result = await runner.run(AgentRunSpec(
+        initial_messages=[{"role": "user", "content": "do task"}],
+        tools=tools,
+        model="test-model",
+        max_iterations=1,
+        max_tool_result_chars=_MAX_TOOL_RESULT_CHARS,
+        goal_active_predicate=lambda: True,
+    ))
+
+    assert result.stop_reason == "max_iterations"
+
+
+@pytest.mark.asyncio
+async def test_runner_does_not_force_continue_on_error():
+    """Even with active goal, an LLM error should exit with stop_reason="error"."""
+    from nanobot.agent.runner import AgentRunner, AgentRunSpec
+
+    provider = MagicMock(spec=LLMProvider)
+    provider.chat_with_retry = AsyncMock(return_value=LLMResponse(
+        content=None, tool_calls=[], usage={},
+        finish_reason="error",
+    ))
+    tools = MagicMock()
+    tools.get_definitions.return_value = []
+
+    runner = AgentRunner(provider)
+    result = await runner.run(AgentRunSpec(
+        initial_messages=[{"role": "user", "content": "do task"}],
+        tools=tools,
+        model="test-model",
+        max_iterations=2,
+        max_tool_result_chars=_MAX_TOOL_RESULT_CHARS,
+        goal_active_predicate=lambda: True,
+    ))
+
+    assert result.stop_reason == "error"
+
+
+@pytest.mark.asyncio
+async def test_runner_uses_custom_goal_continue_message():
+    """Custom goal_continue_message should be injected instead of the default."""
+    from nanobot.agent.runner import AgentRunner, AgentRunSpec
+
+    provider = MagicMock(spec=LLMProvider)
+    provider.chat_with_retry = AsyncMock(return_value=LLMResponse(
+        content="still working", tool_calls=[], usage={},
+    ))
+    tools = MagicMock()
+    tools.get_definitions.return_value = []
+
+    custom_msg = "CUSTOM_CONTINUE_PLEASE"
+
+    runner = AgentRunner(provider)
+    result = await runner.run(AgentRunSpec(
+        initial_messages=[{"role": "user", "content": "do task"}],
+        tools=tools,
+        model="test-model",
+        max_iterations=2,
+        max_tool_result_chars=_MAX_TOOL_RESULT_CHARS,
+        goal_active_predicate=lambda: True,
+        goal_continue_message=custom_msg,
+    ))
+
+    user_msgs = [m for m in result.messages if m.get("role") == "user"]
+    assert any(custom_msg in str(m.get("content", "")) for m in user_msgs)