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:
@@ -0,0 +1,80 @@
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from __future__ import annotations
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from cloud.planner_config import (
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DEFAULT_MODEL_BY_PROVIDER,
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DEFAULT_PROVIDER,
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DEFAULT_TIMEOUT_SECONDS,
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CloudPlannerConfig,
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build_cloud_planner_client,
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load_cloud_planner_config,
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)
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from runtime.tool_calling_client import (
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AnthropicToolCallingClient,
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OpenAIToolCallingClient,
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)
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_NO_RELEVANT_VARS = {"UNRELATED": "1"}
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def test_load_cloud_planner_config_defaults_when_unset() -> None:
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config = load_cloud_planner_config(_NO_RELEVANT_VARS)
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assert config == CloudPlannerConfig(
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provider=DEFAULT_PROVIDER,
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model="",
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timeout=DEFAULT_TIMEOUT_SECONDS,
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)
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assert config.resolved_model() == DEFAULT_MODEL_BY_PROVIDER[DEFAULT_PROVIDER]
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def test_load_cloud_planner_config_selects_provider_and_resolves_default_model() -> (
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None
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):
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config = load_cloud_planner_config({"AI_PLANNER_PROVIDER": "openai"})
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assert config.provider == "openai"
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assert config.resolved_model() == "gpt-5.6"
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def test_load_cloud_planner_config_falls_back_to_default_provider_when_unsupported() -> (
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None
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):
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config = load_cloud_planner_config({"AI_PLANNER_PROVIDER": "not-a-real-provider"})
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assert config.provider == DEFAULT_PROVIDER
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def test_load_cloud_planner_config_model_override_wins_regardless_of_provider() -> None:
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config = load_cloud_planner_config(
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{"AI_PLANNER_PROVIDER": "openai", "AI_PLANNER_MODEL": "custom-model"}
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)
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assert config.resolved_model() == "custom-model"
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def test_load_cloud_planner_config_parses_valid_timeout() -> None:
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config = load_cloud_planner_config({"AI_PLANNER_TIMEOUT_SECONDS": "12.5"})
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assert config.timeout == 12.5
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def test_load_cloud_planner_config_falls_back_to_default_timeout_when_invalid() -> None:
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for value in ["not-a-number", "0", "-5"]:
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config = load_cloud_planner_config(
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{"AI_PLANNER_TIMEOUT_SECONDS": value, **_NO_RELEVANT_VARS}
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)
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assert config.timeout == DEFAULT_TIMEOUT_SECONDS
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def test_build_cloud_planner_client_selects_anthropic_by_default() -> None:
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client = build_cloud_planner_client(CloudPlannerConfig())
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assert isinstance(client, AnthropicToolCallingClient)
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assert client.model == DEFAULT_MODEL_BY_PROVIDER["anthropic"]
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def test_build_cloud_planner_client_selects_openai() -> None:
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client = build_cloud_planner_client(CloudPlannerConfig(provider="openai"))
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assert isinstance(client, OpenAIToolCallingClient)
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assert client.model == DEFAULT_MODEL_BY_PROVIDER["openai"]
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@@ -196,7 +196,12 @@ def create_application(
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else None
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),
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)
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executor = AssignmentExecutor(create_execution_factories(resolved_manager))
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executor = AssignmentExecutor(
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create_execution_factories(
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resolved_manager,
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host_agent_config=resolved_config,
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)
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)
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active_runner = ActiveAssignmentRunner(client, executor)
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processor = AssignmentProcessor(
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client,
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@@ -0,0 +1,109 @@
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"""``ToolCallingClient`` implementation that proxies AI Planner decisions
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through the Cloud Control Plane instead of calling an LLM provider directly.
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Lives in ``host_agent``, not ``runtime`` (design decision D3): the shared
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Runtime package's boundary test
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(``apps/device-host-agent/tests/test_execution.py::test_runtime_owned_packages_do_not_import_host_or_cloud_concerns``)
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forbids ``runtime`` from importing ``cloud`` or ``host_agent``, so this class
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satisfies ``runtime.tool_calling_client.ToolCallingClient`` structurally
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from outside that package instead of living inside it.
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Uses its own synchronous ``httpx.Client`` (mirroring
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``HostAgentEnrollmentClient``'s pattern) rather than wrapping the async
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``HostAgentClient``: ``ToolCallingClient.decide()`` is a synchronous Protocol
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method invoked from a worker thread via ``asyncio.to_thread`` (see
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``host_agent/lease.py``), off the main event loop, so reusing an
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``httpx.AsyncClient`` bound to that loop would require event-loop bridging
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for no real benefit over a plain synchronous client with the same
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host-scoped bearer auth.
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"""
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from __future__ import annotations
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import base64
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from typing import Any
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import httpx
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from cloud.internal_api.models import PlannerDecisionError, PlannerDecisionResponse
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from host_agent.config import HostAgentConfig
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from runtime.tool_calling_client import ToolCallDecision, ToolCallUnavailable
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from runtime.tool_specs import ToolSpec
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class CloudProxyToolCallingClient:
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def __init__(
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self,
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config: HostAgentConfig,
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*,
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http_client: httpx.Client | None = None,
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) -> None:
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self.config = config
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self._owns_client = http_client is None
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self._client = http_client or httpx.Client(base_url=config.control_plane_url)
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def decide(
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self,
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*,
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system_prompt: str,
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user_prompt: str,
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screenshot: bytes | None,
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tools: list[ToolSpec],
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timeout: float,
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) -> ToolCallDecision:
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payload: dict[str, Any] = {
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"host_id": self.config.host_id,
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"system_prompt": system_prompt,
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"user_prompt": user_prompt,
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"screenshot_base64": (
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base64.b64encode(screenshot).decode("ascii")
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if screenshot is not None
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else None
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),
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"tools": [
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{
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"name": spec.name,
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"description": spec.description,
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"parameters": spec.parameters,
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}
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for spec in tools
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],
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"timeout_seconds": timeout,
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}
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try:
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response = self._client.post(
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f"/internal/v1/hosts/{self.config.host_id}/planner/decide",
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json=payload,
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headers={"Authorization": f"Bearer {self.config.token}"},
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timeout=timeout + 5,
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)
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except httpx.HTTPError as exc:
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raise ToolCallUnavailable(str(exc)) from exc
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if response.is_success:
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decoded = PlannerDecisionResponse.model_validate(response.json())
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return ToolCallDecision(
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tool_name=decoded.tool_name,
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arguments=dict(decoded.arguments),
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)
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raise ToolCallUnavailable(_error_detail(response))
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def close(self) -> None:
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if self._owns_client:
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self._client.close()
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def _error_detail(response: httpx.Response) -> str:
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try:
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payload = response.json()
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except ValueError:
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return f"planner-decision request failed with status {response.status_code}"
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try:
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error = PlannerDecisionError.model_validate(payload)
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except Exception:
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detail = payload.get("detail") if isinstance(payload, dict) else None
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return (
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detail
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or f"planner-decision request failed with status {response.status_code}"
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)
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return error.detail
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@@ -12,6 +12,7 @@ class HostAgentConfigurationError(ValueError):
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_LOOPBACK_BIND_HOSTS = frozenset({"127.0.0.1", "localhost", "::1"})
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_AI_PLANNER_TRANSPORTS = frozenset({"direct", "cloud"})
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@dataclass(frozen=True)
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@@ -34,6 +35,7 @@ class HostAgentConfig:
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console_allow_non_loopback: bool = False
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console_session_ttl_seconds: float = 43200.0
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console_history_limit: int = 200
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ai_planner_transport: str = "direct"
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def load_host_agent_config(
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@@ -112,6 +114,9 @@ def load_host_agent_config(
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"HOST_AGENT_CONSOLE_HISTORY_LIMIT",
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200,
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),
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ai_planner_transport=_parse_ai_planner_transport(
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values.get("AI_PLANNER_TRANSPORT")
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),
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)
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if config.max_retry_backoff_seconds < config.retry_backoff_seconds:
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raise HostAgentConfigurationError(
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@@ -129,6 +134,18 @@ def load_host_agent_config(
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return config
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def _parse_ai_planner_transport(value: str | None) -> str:
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if value is None:
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return "direct"
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transport = value.strip().lower()
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if transport not in _AI_PLANNER_TRANSPORTS:
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raise HostAgentConfigurationError(
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"AI_PLANNER_TRANSPORT must be one of "
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f"{', '.join(sorted(_AI_PLANNER_TRANSPORTS))}"
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)
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return transport
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def _positive_float(
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values: Mapping[str, str],
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name: str,
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@@ -5,7 +5,11 @@ from collections.abc import Callable
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from dataclasses import dataclass, replace
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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, load_host_agent_config
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from runtime.ai_planner import AIPlanner
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from runtime.executor import Executor, default_tool_registry
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from runtime.planner import Planner
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from runtime.planner_config import PlannerConfig, load_config as load_planner_config
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from runtime.task import TaskRunner
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from storage.task_metadata import TaskMetadataStore
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@@ -27,14 +31,17 @@ def create_execution_factories(
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workflow_store: WorkflowStore | None = None,
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metadata_store: TaskMetadataStore | None = None,
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timeline: Timeline | None = None,
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host_agent_config: HostAgentConfig | None = None,
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) -> ExecutionFactories:
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shared_workflow_store = workflow_store or WorkflowStore()
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resolved_host_agent_config = host_agent_config
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def create_task_runner() -> TaskRunner:
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return TaskRunner(
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executor=Executor(tools=default_tool_registry(manager=manager)),
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metadata_store=metadata_store,
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timeline=timeline,
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planner=_host_agent_planner(resolved_host_agent_config),
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planner_config=_host_agent_planner_config(),
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)
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@@ -64,3 +71,28 @@ def _host_agent_planner_config() -> PlannerConfig:
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if os.environ.get("AI_PLANNER_ENABLED") is None:
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config = replace(config, enabled=True)
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return config
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def _host_agent_planner(
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host_agent_config: HostAgentConfig | None,
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) -> Planner | None:
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"""Build the `AIPlanner` explicitly when the cloud-proxy transport is
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selected, so its `ToolCallingClient` is a `CloudProxyToolCallingClient`
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instead of a local Anthropic/OpenAI SDK client.
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Returns `None` (letting `TaskRunner` fall back to its own
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`_default_planner()`) for the `direct` transport, which preserves the
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existing default-enabled/direct-to-provider behavior unchanged.
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"""
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planner_config = _host_agent_planner_config()
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if not planner_config.enabled:
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return None
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resolved_config = host_agent_config or load_host_agent_config()
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if resolved_config.ai_planner_transport != "cloud":
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return None
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return AIPlanner(
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client=CloudProxyToolCallingClient(resolved_config),
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config=planner_config,
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)
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@@ -0,0 +1,152 @@
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from __future__ import annotations
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import json
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import httpx
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import pytest
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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 runtime.tool_calling_client import ToolCallDecision, ToolCallUnavailable
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from runtime.tool_specs import ToolSpec
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_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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)
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_TOOLS = [ToolSpec(name="tap", description="tap an element", parameters={})]
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def _client(handler) -> CloudProxyToolCallingClient:
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transport = httpx.MockTransport(handler)
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http_client = httpx.Client(base_url=_CONFIG.control_plane_url, transport=transport)
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return CloudProxyToolCallingClient(_CONFIG, http_client=http_client)
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def test_decide_returns_tool_call_decision_on_success() -> None:
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seen_requests: list[httpx.Request] = []
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def handler(request: httpx.Request) -> httpx.Response:
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seen_requests.append(request)
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return httpx.Response(
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200,
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json={"tool_name": "tap", "arguments": {"x": 1, "y": 2}},
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)
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client = _client(handler)
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decision = client.decide(
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system_prompt="you are a planner",
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user_prompt="tap login",
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screenshot=None,
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tools=_TOOLS,
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timeout=30.0,
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)
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assert decision == ToolCallDecision(tool_name="tap", arguments={"x": 1, "y": 2})
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assert len(seen_requests) == 1
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request = seen_requests[0]
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assert request.url.path == "/internal/v1/hosts/host-a/planner/decide"
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assert request.headers["Authorization"] == "Bearer token-a"
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body = json.loads(request.content)
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assert body["host_id"] == "host-a"
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assert body["system_prompt"] == "you are a planner"
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assert body["screenshot_base64"] is None
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assert body["timeout_seconds"] == 30.0
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def test_decide_base64_encodes_screenshot() -> None:
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seen_requests: list[httpx.Request] = []
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def handler(request: httpx.Request) -> httpx.Response:
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seen_requests.append(request)
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return httpx.Response(200, json={"tool_name": "tap", "arguments": {}})
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client = _client(handler)
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client.decide(
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system_prompt="sp",
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user_prompt="up",
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screenshot=b"hello",
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tools=_TOOLS,
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timeout=10.0,
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)
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body = json.loads(seen_requests[0].content)
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assert body["screenshot_base64"] == "aGVsbG8="
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def test_decide_raises_tool_call_unavailable_on_network_error() -> None:
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def handler(request: httpx.Request) -> httpx.Response:
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raise httpx.ConnectError("connection refused", request=request)
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client = _client(handler)
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with pytest.raises(ToolCallUnavailable):
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client.decide(
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system_prompt="sp",
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user_prompt="up",
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screenshot=None,
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tools=_TOOLS,
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timeout=5.0,
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)
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def test_decide_raises_tool_call_unavailable_on_structured_error_response() -> None:
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def handler(request: httpx.Request) -> httpx.Response:
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return httpx.Response(
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502,
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json={"code": "planner_unavailable", "detail": "provider timed out"},
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)
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client = _client(handler)
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with pytest.raises(ToolCallUnavailable, match="provider timed out"):
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client.decide(
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system_prompt="sp",
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user_prompt="up",
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screenshot=None,
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tools=_TOOLS,
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timeout=5.0,
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)
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def test_decide_raises_tool_call_unavailable_on_unstructured_error_response() -> None:
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def handler(request: httpx.Request) -> httpx.Response:
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return httpx.Response(500, text="internal server error")
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client = _client(handler)
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with pytest.raises(ToolCallUnavailable):
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client.decide(
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system_prompt="sp",
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user_prompt="up",
|
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screenshot=None,
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tools=_TOOLS,
|
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timeout=5.0,
|
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)
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|
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|
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def test_close_closes_an_internally_constructed_http_client() -> None:
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client = CloudProxyToolCallingClient(_CONFIG)
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client.close()
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assert client._client.is_closed
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def test_close_leaves_an_externally_supplied_http_client_open() -> None:
|
||||
"""Only a client built internally (no ``http_client`` override) is closed
|
||||
by ``close()``; a caller-supplied ``http_client`` is left open for the
|
||||
caller to manage."""
|
||||
transport = httpx.MockTransport(lambda request: httpx.Response(200, json={}))
|
||||
external_http_client = httpx.Client(
|
||||
base_url=_CONFIG.control_plane_url, transport=transport
|
||||
)
|
||||
|
||||
client = CloudProxyToolCallingClient(_CONFIG, http_client=external_http_client)
|
||||
client.close()
|
||||
|
||||
assert not external_http_client.is_closed
|
||||
external_http_client.close()
|
||||
@@ -5,6 +5,8 @@ from pathlib import Path
|
||||
import pytest
|
||||
|
||||
from device.manager import DeviceManager
|
||||
from host_agent.cloud_planner_client import CloudProxyToolCallingClient
|
||||
from host_agent.config import HostAgentConfig
|
||||
from host_agent.execution import create_execution_factories
|
||||
from runtime.ai_planner import AIPlanner
|
||||
from runtime.planner import Planner
|
||||
@@ -58,6 +60,54 @@ def test_created_task_runner_honors_explicit_ai_planner_opt_out(
|
||||
assert type(task_runner.planner) is Planner
|
||||
|
||||
|
||||
def test_cloud_transport_builds_ai_planner_with_cloud_proxy_client(
|
||||
tmp_path, monkeypatch: pytest.MonkeyPatch
|
||||
) -> None:
|
||||
monkeypatch.delenv("AI_PLANNER_ENABLED", raising=False)
|
||||
manager = DeviceManager()
|
||||
host_agent_config = HostAgentConfig(
|
||||
control_plane_url="https://control-plane.example",
|
||||
host_id="host-a",
|
||||
token="token-a",
|
||||
ai_planner_transport="cloud",
|
||||
)
|
||||
factories = create_execution_factories(
|
||||
manager,
|
||||
workflow_store=WorkflowStore(tmp_path / "workflows.sqlite3"),
|
||||
host_agent_config=host_agent_config,
|
||||
)
|
||||
|
||||
task_runner = factories.task_runner_factory()
|
||||
|
||||
assert isinstance(task_runner.planner, AIPlanner)
|
||||
assert isinstance(task_runner.planner.client, CloudProxyToolCallingClient)
|
||||
assert task_runner.planner.client.config is host_agent_config
|
||||
|
||||
|
||||
@pytest.mark.parametrize("transport", [None, "direct"])
|
||||
def test_direct_transport_preserves_existing_local_provider_construction(
|
||||
tmp_path, monkeypatch: pytest.MonkeyPatch, transport: str | None
|
||||
) -> None:
|
||||
monkeypatch.delenv("AI_PLANNER_ENABLED", raising=False)
|
||||
manager = DeviceManager()
|
||||
host_agent_config = HostAgentConfig(
|
||||
control_plane_url="https://control-plane.example",
|
||||
host_id="host-a",
|
||||
token="token-a",
|
||||
**({} if transport is None else {"ai_planner_transport": transport}),
|
||||
)
|
||||
factories = create_execution_factories(
|
||||
manager,
|
||||
workflow_store=WorkflowStore(tmp_path / "workflows.sqlite3"),
|
||||
host_agent_config=host_agent_config,
|
||||
)
|
||||
|
||||
task_runner = factories.task_runner_factory()
|
||||
|
||||
assert isinstance(task_runner.planner, AIPlanner)
|
||||
assert not isinstance(task_runner.planner.client, CloudProxyToolCallingClient)
|
||||
|
||||
|
||||
def test_runtime_owned_packages_do_not_import_host_or_cloud_concerns() -> None:
|
||||
root = Path(__file__).resolve().parents[3]
|
||||
forbidden = ("import cloud", "from cloud", "import host_agent", "from host_agent")
|
||||
|
||||
Reference in New Issue
Block a user