create_task_runner() built TaskRunner's observer/screenshot_provider by
calling describe_screen(device_id)/take_screenshot(device_id) without
manager=, so both silently fell back to the process-global DEFAULT_MANAGER
singleton instead of the Host Agent's real, device-populated DeviceManager.
DEFAULT_MANAGER never has any device registered, so every task's first step
raised DeviceNotFoundError even though the console (which does pass
manager=) showed the same device as connected. Deterministic on every task,
independent of process count.
Add regression tests confirming both lambdas now resolve devices via the
configured manager; verified each fails with the original DeviceNotFoundError
symptom when the fix is reverted.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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.
- Host Agent now defaults AI_PLANNER_ENABLED=true (opt-out via env),
scoped to apps/device-host-agent/host_agent/execution.py only; the
shared runtime.planner_config default (disabled) is unchanged.
- Add openspec proposal for cloud-planner-proxy: centralize LLM
provider config/credentials on the Cloud Control Plane and let the
Host Agent proxy AI Planner decisions through it instead of holding
provider API keys locally. Proposal only, no implementation yet.
q792602257
