8 Commits

Include renames

Author	SHA1	Message	Date
showtan001	dd8df33910	Log task planner conversations locally	2026-08-30 22:38:28 +08:00
q792602257	358f4623ba	feat(planner): add execution context to prompts	2026-07-16 10:25:20 +08:00
q792602257	77d4813bb2	feat(host-agent): make execution history authoritative	2026-07-15 11:46:27 +08:00
q792602257	30f09b6268	feat(host-agent): default planner transport to cloud	2026-07-14 20:42:27 +08:00
q792602257andClaude Sonnet 5	08cef7ca3c	fix(host-agent): thread device manager into task runner observer/screenshot ... 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>	2026-07-14 16:35:48 +08:00
q792602257	a68f609453	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.	2026-07-13 21:27:48 +08:00
q792602257	1107ace89c	Default-enable AI Planner in Host Agent; propose cloud-planner-proxy ... - 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.	2026-07-13 20:50:35 +08:00
q792602257	ab538513b0	feat(host-agent): compose execution factories	2026-07-12 18:50:21 +08:00