showtan001
5458f3b8a4
Tests / Test apps.device-host-agent.tests.test_mcp_token.test_load_or_create_concurrent_calls_do_not_corrupt failed
117 lines
4.1 KiB
Python
117 lines
4.1 KiB
Python
from __future__ import annotations
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from typing import TYPE_CHECKING, Any
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from core.errors import TaskFailedError
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from core.models import Scene
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from runtime.context import TaskContext
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from runtime.planner import PlannedStep, Planner
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from runtime.planner_config import PlannerConfig, load_config
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from runtime.planner_prompts import PLANNER_SYSTEM_PROMPT, planner_user_prompt
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from runtime.tool_calling_client import ToolCallingClient, build_client
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from runtime.tool_specs import ALL_TOOL_SPECS
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if TYPE_CHECKING:
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from world.models import WorldState
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FINISH_TASK_TOOL = "finish_task"
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class AIPlanner(Planner):
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def __init__(
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self,
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*,
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client: ToolCallingClient | None = None,
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config: PlannerConfig | None = None,
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) -> None:
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self.config = config or load_config()
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self.client = client or build_client(self.config)
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def plan(
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self,
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*,
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goal: str,
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scene: Scene,
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context: TaskContext,
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world: "WorldState | None" = None,
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screenshot: bytes | None = None,
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) -> list[PlannedStep]:
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scene_json = _without_ocr(scene.to_dict()) if self.config.multimodal else scene.to_dict()
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user_prompt = planner_user_prompt(
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goal=goal,
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scene_json=scene_json,
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history_summary=_history_summary(world),
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device_platform=context.device_platform,
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)
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if context.step_results and not context.step_results[-1].success:
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user_prompt += (
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"\n\nThe previous tool call failed. Diagnose the failure and choose a "
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"corrected action or finish the task if it cannot proceed.\n"
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f"Previous failure: {context.step_results[-1].error or 'unknown error'}"
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)
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decision = self.client.decide(
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system_prompt=PLANNER_SYSTEM_PROMPT,
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user_prompt=user_prompt,
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screenshot=screenshot,
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tools=ALL_TOOL_SPECS,
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timeout=self.config.timeout,
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)
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if decision.tool_name == FINISH_TASK_TOOL:
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if decision.arguments.get("success"):
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return []
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raise TaskFailedError(decision.arguments.get("reason") or "task failed")
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return [
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PlannedStep(
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action=decision.tool_name,
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description=(
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f"AI planner: {decision.purpose}"
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if decision.purpose
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else f"AI planner: {decision.tool_name}({decision.arguments})"
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),
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args=dict(decision.arguments),
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expected_text=decision.expected_outcome,
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purpose=decision.purpose,
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expected_outcome=decision.expected_outcome,
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prompt=decision.user_prompt or user_prompt,
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rationale=decision.text_output,
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thinking=decision.thinking,
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)
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]
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def goal_reached(self, *, goal: str, scene: Scene, context: TaskContext) -> bool:
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# Completion is signaled exclusively via the finish_task tool call
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# (mapped to an empty plan above), never via this hook.
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return False
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def _history_summary(world: "WorldState | None") -> list[dict[str, Any]]:
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if world is None:
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return []
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return [
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{
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"page": event.page,
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"action": event.action,
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"arguments": dict(event.arguments),
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"rationale": event.rationale,
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"purpose": event.purpose,
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"expected_outcome": event.expected_outcome,
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"success": event.success,
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}
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for event in world.history
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]
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def _without_ocr(scene_json: dict[str, Any]) -> dict[str, Any]:
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cleaned = dict(scene_json)
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elements = cleaned.get("elements")
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if isinstance(elements, list):
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cleaned["elements"] = [
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{key: value for key, value in element.items() if key not in {"source", "confidence", "foreground_color", "background_color"}}
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for element in elements
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if isinstance(element, dict) and element.get("source") != "ocr"
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]
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cleaned.pop("ocr_elements", None)
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return cleaned
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