feat(box): add sandbox_exec tool loop for local-agent calculations

tests/unit_tests/provider/test_localagent_sandbox_exec.py

@@ -0,0 +1,149 @@
+from __future__ import annotations
+
+import json
+from types import SimpleNamespace
+from unittest.mock import AsyncMock, Mock
+
+import pytest
+
+import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
+import langbot_plugin.api.entities.builtin.provider.message as provider_message
+import langbot_plugin.api.entities.builtin.provider.session as provider_session
+
+from langbot.pkg.provider.runners.localagent import LocalAgentRunner
+
+
+class RecordingProvider:
+    def __init__(self):
+        self.requests: list[dict] = []
+
+    async def invoke_llm(self, query, model, messages, funcs, extra_args=None, remove_think=None):
+        self.requests.append(
+            {
+                'messages': list(messages),
+                'funcs': list(funcs),
+                'remove_think': remove_think,
+            }
+        )
+
+        if len(self.requests) == 1:
+            return provider_message.Message(
+                role='assistant',
+                content='Let me calculate that exactly.',
+                tool_calls=[
+                    provider_message.ToolCall(
+                        id='call-1',
+                        type='function',
+                        function=provider_message.FunctionCall(
+                            name='sandbox_exec',
+                            arguments=json.dumps(
+                                {
+                                    'cmd': (
+                                        "python - <<'PY'\n"
+                                        "nums = [1, 2, 3, 4]\n"
+                                        'print(sum(nums) / len(nums))\n'
+                                        'PY'
+                                    )
+                                }
+                            ),
+                        ),
+                    )
+                ],
+            )
+
+        tool_result = json.loads(messages[-1].content)
+        return provider_message.Message(
+            role='assistant',
+            content=f"The average is {tool_result['stdout']}.",
+        )
+
+
+def make_query() -> pipeline_query.Query:
+    adapter = AsyncMock()
+    adapter.is_stream_output_supported = AsyncMock(return_value=False)
+
+    return pipeline_query.Query.model_construct(
+        query_id='avg-query',
+        launcher_type=provider_session.LauncherTypes.PERSON,
+        launcher_id=12345,
+        sender_id=12345,
+        message_chain=[],
+        message_event=None,
+        adapter=adapter,
+        pipeline_uuid='pipeline-uuid',
+        bot_uuid='bot-uuid',
+        pipeline_config={
+            'ai': {
+                'runner': {'runner': 'local-agent'},
+                'local-agent': {'model': {'primary': 'test-model-uuid', 'fallbacks': []}, 'prompt': 'test-prompt'},
+            },
+            'output': {'misc': {'remove-think': False}},
+        },
+        prompt=SimpleNamespace(messages=[]),
+        messages=[],
+        user_message=provider_message.Message(
+            role='user',
+            content='Please calculate the average of 1, 2, 3, and 4.',
+        ),
+        use_funcs=[SimpleNamespace(name='sandbox_exec')],
+        use_llm_model_uuid='test-model-uuid',
+        variables={},
+    )
+
+
+@pytest.mark.asyncio
+async def test_localagent_uses_sandbox_exec_for_exact_calculation():
+    provider = RecordingProvider()
+    model = SimpleNamespace(
+        provider=provider,
+        model_entity=SimpleNamespace(
+            uuid='test-model-uuid',
+            name='test-model',
+            abilities=['func_call'],
+            extra_args={},
+        ),
+    )
+
+    tool_manager = SimpleNamespace(
+        execute_func_call=AsyncMock(
+            return_value={
+                'session_id': 'avg-query',
+                'backend': 'podman',
+                'status': 'completed',
+                'ok': True,
+                'exit_code': 0,
+                'stdout': '2.5',
+                'stderr': '',
+                'duration_ms': 18,
+            }
+        )
+    )
+
+    app = SimpleNamespace(
+        logger=Mock(),
+        model_mgr=SimpleNamespace(get_model_by_uuid=AsyncMock(return_value=model)),
+        tool_mgr=tool_manager,
+        rag_mgr=SimpleNamespace(),
+    )
+
+    runner = LocalAgentRunner(app, pipeline_config={})
+    query = make_query()
+
+    results = [message async for message in runner.run(query)]
+
+    assert [message.role for message in results] == ['assistant', 'tool', 'assistant']
+    assert results[-1].content == 'The average is 2.5.'
+
+    tool_manager.execute_func_call.assert_awaited_once()
+    tool_name, tool_parameters = tool_manager.execute_func_call.await_args.args[:2]
+    assert tool_name == 'sandbox_exec'
+    assert "print(sum(nums) / len(nums))" in tool_parameters['cmd']
+
+    first_request = provider.requests[0]
+    assert any(
+        message.role == 'system'
+        and 'sandbox_exec' in str(message.content)
+        and 'exact calculations' in str(message.content)
+        for message in first_request['messages']
+    )
+    assert [tool.name for tool in first_request['funcs']] == ['sandbox_exec']

tests/unit_tests/provider/test_tool_manager_native.py

@@ -0,0 +1,63 @@
+from __future__ import annotations
+
+from types import SimpleNamespace
+from unittest.mock import Mock
+
+import pytest
+
+import langbot_plugin.api.entities.builtin.resource.tool as resource_tool
+
+from langbot.pkg.provider.tools.toolmgr import ToolManager
+
+
+class StubLoader:
+    def __init__(self, tools: list[resource_tool.LLMTool] | None = None, invoke_result=None):
+        self._tools = tools or []
+        self._invoke_result = invoke_result
+
+    async def get_tools(self, *_args, **_kwargs):
+        return self._tools
+
+    async def has_tool(self, name: str) -> bool:
+        return any(tool.name == name for tool in self._tools)
+
+    async def invoke_tool(self, name: str, parameters: dict, query):
+        return self._invoke_result(name, parameters, query) if callable(self._invoke_result) else self._invoke_result
+
+    async def shutdown(self):
+        return None
+
+
+def make_tool(name: str) -> resource_tool.LLMTool:
+    return resource_tool.LLMTool(
+        name=name,
+        human_desc=name,
+        description=name,
+        parameters={'type': 'object', 'properties': {}},
+        func=lambda parameters: parameters,
+    )
+
+
+@pytest.mark.asyncio
+async def test_tool_manager_lists_native_tools_first():
+    manager = ToolManager(SimpleNamespace())
+    manager.native_tool_loader = StubLoader([make_tool('sandbox_exec')])
+    manager.plugin_tool_loader = StubLoader([make_tool('plugin_tool')])
+    manager.mcp_tool_loader = StubLoader([make_tool('mcp_tool')])
+
+    tools = await manager.get_all_tools()
+
+    assert [tool.name for tool in tools] == ['sandbox_exec', 'plugin_tool', 'mcp_tool']
+
+
+@pytest.mark.asyncio
+async def test_tool_manager_routes_native_tool_calls():
+    app = SimpleNamespace()
+    manager = ToolManager(app)
+    manager.native_tool_loader = StubLoader([make_tool('sandbox_exec')], invoke_result={'backend': 'fake'})
+    manager.plugin_tool_loader = StubLoader([make_tool('plugin_tool')])
+    manager.mcp_tool_loader = StubLoader([make_tool('mcp_tool')])
+
+    result = await manager.execute_func_call('sandbox_exec', {'cmd': 'pwd'}, query=Mock())
+
+    assert result == {'backend': 'fake'}