Implement cloud-planner-proxy: AI planner routes through Cloud API
Implements all 19 tasks of the cloud-planner-proxy OpenSpec change:
- Cloud API: cloud.planner_config (CloudPlannerConfig, load/build helpers)
reusing runtime.tool_calling_client provider clients (no new dependency
needed -- device-cloud-platform already depends on device-agent-runtime).
- Cloud API: new host-scoped POST /internal/v1/hosts/{host_id}/planner/decide
internal endpoint, reusing existing bearer auth; logs only metadata
(host id, tool name, latency, error class), never prompt/screenshot
content.
- Host Agent: new AI_PLANNER_TRANSPORT config (direct default | cloud) and
host_agent/cloud_planner_client.py::CloudProxyToolCallingClient, a
synchronous ToolCallingClient implementation (structural, not importing
runtime) that calls the new endpoint via its own httpx.Client -- avoids
bridging the async HostAgentClient across the worker-thread boundary
that AIPlanner.plan() runs in (asyncio.to_thread in lease.py).
- Host Agent wiring: create_execution_factories()/_host_agent_planner()
select the cloud-proxy client only when AI_PLANNER_TRANSPORT=cloud;
direct/unset transport is unchanged (still the default).
- Tests: 22 new tests across Cloud API config, the new endpoint, the new
client, and transport-selection wiring; full non-integration suite
(492 tests) passes with no regressions.
- Docs: docs/CLOUD_DEPLOYMENT.md documents the cloud transport, its
trade-offs, and the credential split between Host Agent and Cloud API.
proposal.md/design.md were corrected during implementation to reflect two
findings: no new anthropic/openai dependency is actually needed, and
CloudProxyToolCallingClient uses its own sync httpx.Client rather than a
new HostAgentClient method, per the thread-boundary reasoning above.
This commit is contained in:
@@ -5,6 +5,8 @@ from pathlib import Path
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import pytest
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from device.manager import DeviceManager
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from host_agent.cloud_planner_client import CloudProxyToolCallingClient
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from host_agent.config import HostAgentConfig
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from host_agent.execution import create_execution_factories
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from runtime.ai_planner import AIPlanner
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from runtime.planner import Planner
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@@ -58,6 +60,54 @@ def test_created_task_runner_honors_explicit_ai_planner_opt_out(
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assert type(task_runner.planner) is Planner
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def test_cloud_transport_builds_ai_planner_with_cloud_proxy_client(
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tmp_path, monkeypatch: pytest.MonkeyPatch
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) -> None:
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monkeypatch.delenv("AI_PLANNER_ENABLED", raising=False)
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manager = DeviceManager()
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host_agent_config = HostAgentConfig(
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control_plane_url="https://control-plane.example",
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host_id="host-a",
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token="token-a",
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ai_planner_transport="cloud",
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)
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factories = create_execution_factories(
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manager,
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workflow_store=WorkflowStore(tmp_path / "workflows.sqlite3"),
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host_agent_config=host_agent_config,
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)
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task_runner = factories.task_runner_factory()
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assert isinstance(task_runner.planner, AIPlanner)
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assert isinstance(task_runner.planner.client, CloudProxyToolCallingClient)
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assert task_runner.planner.client.config is host_agent_config
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@pytest.mark.parametrize("transport", [None, "direct"])
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def test_direct_transport_preserves_existing_local_provider_construction(
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tmp_path, monkeypatch: pytest.MonkeyPatch, transport: str | None
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) -> None:
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monkeypatch.delenv("AI_PLANNER_ENABLED", raising=False)
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manager = DeviceManager()
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host_agent_config = HostAgentConfig(
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control_plane_url="https://control-plane.example",
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host_id="host-a",
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token="token-a",
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**({} if transport is None else {"ai_planner_transport": transport}),
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)
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factories = create_execution_factories(
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manager,
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workflow_store=WorkflowStore(tmp_path / "workflows.sqlite3"),
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host_agent_config=host_agent_config,
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)
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task_runner = factories.task_runner_factory()
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assert isinstance(task_runner.planner, AIPlanner)
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assert not isinstance(task_runner.planner.client, CloudProxyToolCallingClient)
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def test_runtime_owned_packages_do_not_import_host_or_cloud_concerns() -> None:
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root = Path(__file__).resolve().parents[3]
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forbidden = ("import cloud", "from cloud", "import host_agent", "from host_agent")
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