chore: update nanobot to 0.1.4.post6
This commit is contained in:
qixinbo
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"""Tests for the shared agent runner and its integration contracts."""
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from __future__ import annotations
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from unittest.mock import AsyncMock, MagicMock, patch
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import pytest
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from nanobot.providers.base import LLMResponse, ToolCallRequest
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def _make_loop(tmp_path):
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from nanobot.agent.loop import AgentLoop
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from nanobot.bus.queue import MessageBus
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bus = MessageBus()
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provider = MagicMock()
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provider.get_default_model.return_value = "test-model"
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with patch("nanobot.agent.loop.ContextBuilder"), \
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patch("nanobot.agent.loop.SessionManager"), \
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patch("nanobot.agent.loop.SubagentManager") as MockSubMgr:
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MockSubMgr.return_value.cancel_by_session = AsyncMock(return_value=0)
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loop = AgentLoop(bus=bus, provider=provider, workspace=tmp_path)
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return loop
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@pytest.mark.asyncio
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async def test_runner_preserves_reasoning_fields_and_tool_results():
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from nanobot.agent.runner import AgentRunSpec, AgentRunner
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provider = MagicMock()
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captured_second_call: list[dict] = []
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call_count = {"n": 0}
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async def chat_with_retry(*, messages, **kwargs):
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call_count["n"] += 1
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if call_count["n"] == 1:
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return LLMResponse(
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content="thinking",
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tool_calls=[ToolCallRequest(id="call_1", name="list_dir", arguments={"path": "."})],
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reasoning_content="hidden reasoning",
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thinking_blocks=[{"type": "thinking", "thinking": "step"}],
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usage={"prompt_tokens": 5, "completion_tokens": 3},
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)
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captured_second_call[:] = messages
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return LLMResponse(content="done", tool_calls=[], usage={})
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provider.chat_with_retry = chat_with_retry
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tools = MagicMock()
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tools.get_definitions.return_value = []
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tools.execute = AsyncMock(return_value="tool result")
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runner = AgentRunner(provider)
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result = await runner.run(AgentRunSpec(
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initial_messages=[
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{"role": "system", "content": "system"},
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{"role": "user", "content": "do task"},
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],
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tools=tools,
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model="test-model",
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max_iterations=3,
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))
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assert result.final_content == "done"
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assert result.tools_used == ["list_dir"]
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assert result.tool_events == [
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{"name": "list_dir", "status": "ok", "detail": "tool result"}
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]
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assistant_messages = [
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msg for msg in captured_second_call
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if msg.get("role") == "assistant" and msg.get("tool_calls")
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]
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assert len(assistant_messages) == 1
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assert assistant_messages[0]["reasoning_content"] == "hidden reasoning"
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assert assistant_messages[0]["thinking_blocks"] == [{"type": "thinking", "thinking": "step"}]
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assert any(
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msg.get("role") == "tool" and msg.get("content") == "tool result"
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for msg in captured_second_call
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)
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@pytest.mark.asyncio
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async def test_runner_calls_hooks_in_order():
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from nanobot.agent.hook import AgentHook, AgentHookContext
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from nanobot.agent.runner import AgentRunSpec, AgentRunner
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provider = MagicMock()
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call_count = {"n": 0}
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events: list[tuple] = []
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async def chat_with_retry(**kwargs):
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call_count["n"] += 1
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if call_count["n"] == 1:
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return LLMResponse(
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content="thinking",
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tool_calls=[ToolCallRequest(id="call_1", name="list_dir", arguments={"path": "."})],
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)
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return LLMResponse(content="done", tool_calls=[], usage={})
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provider.chat_with_retry = chat_with_retry
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tools = MagicMock()
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tools.get_definitions.return_value = []
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tools.execute = AsyncMock(return_value="tool result")
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class RecordingHook(AgentHook):
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async def before_iteration(self, context: AgentHookContext) -> None:
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events.append(("before_iteration", context.iteration))
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async def before_execute_tools(self, context: AgentHookContext) -> None:
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events.append((
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"before_execute_tools",
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context.iteration,
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[tc.name for tc in context.tool_calls],
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))
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async def after_iteration(self, context: AgentHookContext) -> None:
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events.append((
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"after_iteration",
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context.iteration,
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context.final_content,
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list(context.tool_results),
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list(context.tool_events),
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context.stop_reason,
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))
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def finalize_content(self, context: AgentHookContext, content: str | None) -> str | None:
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events.append(("finalize_content", context.iteration, content))
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return content.upper() if content else content
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runner = AgentRunner(provider)
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result = await runner.run(AgentRunSpec(
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initial_messages=[],
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tools=tools,
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model="test-model",
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max_iterations=3,
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hook=RecordingHook(),
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))
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assert result.final_content == "DONE"
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assert events == [
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("before_iteration", 0),
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("before_execute_tools", 0, ["list_dir"]),
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(
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"after_iteration",
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0,
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None,
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["tool result"],
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[{"name": "list_dir", "status": "ok", "detail": "tool result"}],
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None,
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),
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("before_iteration", 1),
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("finalize_content", 1, "done"),
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("after_iteration", 1, "DONE", [], [], "completed"),
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]
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@pytest.mark.asyncio
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async def test_runner_streaming_hook_receives_deltas_and_end_signal():
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from nanobot.agent.hook import AgentHook, AgentHookContext
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from nanobot.agent.runner import AgentRunSpec, AgentRunner
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provider = MagicMock()
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streamed: list[str] = []
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endings: list[bool] = []
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async def chat_stream_with_retry(*, on_content_delta, **kwargs):
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await on_content_delta("he")
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await on_content_delta("llo")
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return LLMResponse(content="hello", tool_calls=[], usage={})
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provider.chat_stream_with_retry = chat_stream_with_retry
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provider.chat_with_retry = AsyncMock()
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tools = MagicMock()
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tools.get_definitions.return_value = []
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class StreamingHook(AgentHook):
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def wants_streaming(self) -> bool:
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return True
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async def on_stream(self, context: AgentHookContext, delta: str) -> None:
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streamed.append(delta)
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async def on_stream_end(self, context: AgentHookContext, *, resuming: bool) -> None:
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endings.append(resuming)
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runner = AgentRunner(provider)
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result = await runner.run(AgentRunSpec(
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initial_messages=[],
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tools=tools,
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model="test-model",
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max_iterations=1,
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hook=StreamingHook(),
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))
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assert result.final_content == "hello"
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assert streamed == ["he", "llo"]
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assert endings == [False]
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provider.chat_with_retry.assert_not_awaited()
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@pytest.mark.asyncio
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async def test_runner_returns_max_iterations_fallback():
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from nanobot.agent.runner import AgentRunSpec, AgentRunner
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provider = MagicMock()
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provider.chat_with_retry = AsyncMock(return_value=LLMResponse(
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content="still working",
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tool_calls=[ToolCallRequest(id="call_1", name="list_dir", arguments={"path": "."})],
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))
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tools = MagicMock()
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tools.get_definitions.return_value = []
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tools.execute = AsyncMock(return_value="tool result")
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runner = AgentRunner(provider)
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result = await runner.run(AgentRunSpec(
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initial_messages=[],
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tools=tools,
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model="test-model",
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max_iterations=2,
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))
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assert result.stop_reason == "max_iterations"
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assert result.final_content == (
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"I reached the maximum number of tool call iterations (2) "
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"without completing the task. You can try breaking the task into smaller steps."
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)
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@pytest.mark.asyncio
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async def test_runner_returns_structured_tool_error():
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from nanobot.agent.runner import AgentRunSpec, AgentRunner
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provider = MagicMock()
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provider.chat_with_retry = AsyncMock(return_value=LLMResponse(
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content="working",
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tool_calls=[ToolCallRequest(id="call_1", name="list_dir", arguments={})],
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))
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tools = MagicMock()
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tools.get_definitions.return_value = []
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tools.execute = AsyncMock(side_effect=RuntimeError("boom"))
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runner = AgentRunner(provider)
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result = await runner.run(AgentRunSpec(
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initial_messages=[],
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tools=tools,
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model="test-model",
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max_iterations=2,
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fail_on_tool_error=True,
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))
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assert result.stop_reason == "tool_error"
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assert result.error == "Error: RuntimeError: boom"
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assert result.tool_events == [
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{"name": "list_dir", "status": "error", "detail": "boom"}
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]
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@pytest.mark.asyncio
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async def test_loop_max_iterations_message_stays_stable(tmp_path):
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loop = _make_loop(tmp_path)
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loop.provider.chat_with_retry = AsyncMock(return_value=LLMResponse(
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content="working",
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tool_calls=[ToolCallRequest(id="call_1", name="list_dir", arguments={})],
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))
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loop.tools.get_definitions = MagicMock(return_value=[])
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loop.tools.execute = AsyncMock(return_value="ok")
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loop.max_iterations = 2
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final_content, _, _ = await loop._run_agent_loop([])
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assert final_content == (
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"I reached the maximum number of tool call iterations (2) "
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"without completing the task. You can try breaking the task into smaller steps."
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)
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@pytest.mark.asyncio
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async def test_loop_stream_filter_handles_think_only_prefix_without_crashing(tmp_path):
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loop = _make_loop(tmp_path)
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deltas: list[str] = []
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endings: list[bool] = []
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async def chat_stream_with_retry(*, on_content_delta, **kwargs):
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await on_content_delta("<think>hidden")
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await on_content_delta("</think>Hello")
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return LLMResponse(content="<think>hidden</think>Hello", tool_calls=[], usage={})
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loop.provider.chat_stream_with_retry = chat_stream_with_retry
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async def on_stream(delta: str) -> None:
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deltas.append(delta)
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async def on_stream_end(*, resuming: bool = False) -> None:
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endings.append(resuming)
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final_content, _, _ = await loop._run_agent_loop(
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[],
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on_stream=on_stream,
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on_stream_end=on_stream_end,
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)
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assert final_content == "Hello"
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assert deltas == ["Hello"]
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assert endings == [False]
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@pytest.mark.asyncio
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async def test_subagent_max_iterations_announces_existing_fallback(tmp_path, monkeypatch):
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from nanobot.agent.subagent import SubagentManager
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from nanobot.bus.queue import MessageBus
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bus = MessageBus()
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provider = MagicMock()
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provider.get_default_model.return_value = "test-model"
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provider.chat_with_retry = AsyncMock(return_value=LLMResponse(
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content="working",
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tool_calls=[ToolCallRequest(id="call_1", name="list_dir", arguments={})],
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))
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mgr = SubagentManager(provider=provider, workspace=tmp_path, bus=bus)
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mgr._announce_result = AsyncMock()
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async def fake_execute(self, name, arguments):
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return "tool result"
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monkeypatch.setattr("nanobot.agent.tools.registry.ToolRegistry.execute", fake_execute)
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await mgr._run_subagent("sub-1", "do task", "label", {"channel": "test", "chat_id": "c1"})
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mgr._announce_result.assert_awaited_once()
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args = mgr._announce_result.await_args.args
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assert args[3] == "Task completed but no final response was generated."
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assert args[5] == "ok"
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