add claw-code-agent/src/plan_runtime.py and claw-code-agent/src/background_runtime.py. The agent now has a real
persistent plan runtime with update_plan, plan_get, and plan_clear, plus plan-to-task sync wired through claw-code-agent/src/ agent_tools.py, claw-code-agent/src/agent_runtime.py, claw-code-agent/src/agent_context.py, claw-code-agent/src/agent_prompting.py, and claw-code-agent/src/ agent_slash_commands.py. New local plan slash commands are /plan and /planner.
This commit is contained in:
Abdelrahman Abdallah
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from __future__ import annotations
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import json
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import tempfile
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import unittest
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from pathlib import Path
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from unittest.mock import patch
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from src.agent_runtime import LocalCodingAgent
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from src.agent_tools import build_tool_context, default_tool_registry, execute_tool
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from src.agent_types import AgentPermissions, AgentRuntimeConfig, ModelConfig
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from src.plan_runtime import PlanRuntime
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from src.task_runtime import TaskRuntime
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class FakeHTTPResponse:
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def __init__(self, payload: dict[str, object]) -> None:
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self.payload = payload
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def read(self) -> bytes:
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return json.dumps(self.payload).encode('utf-8')
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def __enter__(self) -> 'FakeHTTPResponse':
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return self
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def __exit__(self, exc_type, exc, tb) -> None:
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return None
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def make_urlopen_side_effect(responses: list[dict[str, object]]):
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queued = [FakeHTTPResponse(payload) for payload in responses]
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def _fake_urlopen(request_obj, timeout=None): # noqa: ANN001
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return queued.pop(0)
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return _fake_urlopen
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class PlanRuntimeTests(unittest.TestCase):
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def test_runtime_persists_and_syncs_plan_to_tasks(self) -> None:
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with tempfile.TemporaryDirectory() as tmp_dir:
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workspace = Path(tmp_dir)
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task_runtime = TaskRuntime.from_workspace(workspace)
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plan_runtime = PlanRuntime.from_workspace(workspace)
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mutation = plan_runtime.update_plan(
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[
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{
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'step': 'Inspect the runtime loop',
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'status': 'in_progress',
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'description': 'Read the core agent files first.',
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},
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{
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'step': 'Patch the tool registry',
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'status': 'pending',
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},
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],
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explanation='Work through the runtime in two phases.',
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task_runtime=task_runtime,
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)
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rendered_plan = plan_runtime.render_plan()
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rendered_tasks = task_runtime.render_tasks()
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self.assertEqual(mutation.after_count, 2)
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self.assertEqual(mutation.synced_tasks, 2)
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self.assertIn('Inspect the runtime loop', rendered_plan)
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self.assertIn('Work through the runtime in two phases.', rendered_plan)
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self.assertIn('Inspect the runtime loop', rendered_tasks)
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def test_plan_tools_execute_against_runtime(self) -> None:
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with tempfile.TemporaryDirectory() as tmp_dir:
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workspace = Path(tmp_dir)
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task_runtime = TaskRuntime.from_workspace(workspace)
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plan_runtime = PlanRuntime.from_workspace(workspace)
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context = build_tool_context(
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AgentRuntimeConfig(
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cwd=workspace,
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permissions=AgentPermissions(allow_file_write=True),
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),
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plan_runtime=plan_runtime,
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task_runtime=task_runtime,
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)
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update_result = execute_tool(
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default_tool_registry(),
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'update_plan',
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{
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'explanation': 'Follow the current plan.',
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'items': [
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{'step': 'Inspect the workspace', 'status': 'completed'},
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{'step': 'Implement the fix', 'status': 'in_progress'},
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],
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},
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context,
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)
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get_result = execute_tool(
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default_tool_registry(),
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'plan_get',
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{},
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context,
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)
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clear_result = execute_tool(
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default_tool_registry(),
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'plan_clear',
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{'sync_tasks': True},
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context,
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)
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self.assertTrue(update_result.ok)
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self.assertEqual(update_result.metadata.get('total_steps'), 2)
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self.assertEqual(update_result.metadata.get('synced_tasks'), 2)
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self.assertIn('# Plan', get_result.content)
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self.assertTrue(clear_result.ok)
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self.assertEqual(clear_result.metadata.get('total_steps'), 0)
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def test_agent_can_use_update_plan_tool_in_model_loop(self) -> None:
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responses = [
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{
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'choices': [
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{
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'message': {
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'role': 'assistant',
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'content': 'I will store the plan first.',
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'tool_calls': [
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{
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'id': 'call_1',
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'type': 'function',
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'function': {
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'name': 'update_plan',
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'arguments': json.dumps(
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{
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'explanation': 'Start with a plan.',
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'items': [
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{
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'step': 'Inspect the current files',
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'status': 'in_progress',
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},
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{
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'step': 'Apply the code changes',
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'status': 'pending',
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},
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],
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}
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),
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},
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}
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],
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},
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'finish_reason': 'tool_calls',
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}
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],
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'usage': {'prompt_tokens': 8, 'completion_tokens': 3},
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},
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{
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'choices': [
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{
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'message': {
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'role': 'assistant',
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'content': 'The plan was stored successfully.',
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},
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'finish_reason': 'stop',
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}
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],
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'usage': {'prompt_tokens': 6, 'completion_tokens': 3},
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},
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]
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with tempfile.TemporaryDirectory() as tmp_dir:
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workspace = Path(tmp_dir)
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with patch(
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'src.openai_compat.request.urlopen',
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side_effect=make_urlopen_side_effect(responses),
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):
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agent = LocalCodingAgent(
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model_config=ModelConfig(
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model='Qwen/Qwen3-Coder-30B-A3B-Instruct',
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base_url='http://127.0.0.1:8000/v1',
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),
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runtime_config=AgentRuntimeConfig(
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cwd=workspace,
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permissions=AgentPermissions(allow_file_write=True),
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),
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)
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result = agent.run('Store the current plan')
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self.assertTrue((workspace / '.port_sessions' / 'plan_runtime.json').exists())
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self.assertEqual(result.final_output, 'The plan was stored successfully.')
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self.assertEqual(result.tool_calls, 1)
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tool_message = next(
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message for message in result.transcript if message.get('role') == 'tool'
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)
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self.assertIn('update_plan', tool_message.get('content', ''))
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