275 lines
10 KiB
Python
275 lines
10 KiB
Python
"""Agent OS environment observation layer."""
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from __future__ import annotations
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from dataclasses import dataclass, field
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from typing import Any
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from ...schemas.pmflow_agent_runtime import (
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PMFlowAgentObservationPacket,
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PMFlowAgentStepPacket,
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new_pmflow_agent_id,
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)
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from ...schemas.pmflow_ai_agent_runtime import PMFlowAIAgentObservation, PMFlowAIAgentStepProposal
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from ...schemas.rag import RAGAskRequest
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from ..pmflow_ai_agent_runtime.agent_tool_registry import PMFlowAIAgentToolRegistry
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@dataclass(slots=True)
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class PMFlowAgentEnvironmentResult:
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steps: list[PMFlowAgentStepPacket] = field(default_factory=list)
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observations: list[PMFlowAgentObservationPacket] = field(default_factory=list)
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def customer_safe_payload(self) -> dict[str, Any]:
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return {
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"packet_version": "pmflow_agent_environment.v1",
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"visibility": "customer",
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"steps": [item.model_dump(mode="json", exclude_none=True) for item in self.steps],
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"observations": [item.model_dump(mode="json", exclude_none=True) for item in self.observations],
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}
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class PMFlowAgentEnvironmentService:
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"""Read the initial customer-safe environment for a durable Agent OS run.
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This layer does not infer business intent from text. It only consumes
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structured context, explicit anchors and registered read-only tools.
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"""
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def __init__(self, *, db: Any, tenant_id: int, tool_registry: Any | None = None) -> None:
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self.db = db
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self.tenant_id = int(tenant_id or 1)
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self.tool_registry = tool_registry or PMFlowAIAgentToolRegistry(db=db, tenant_id=self.tenant_id)
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async def observe_initial(
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self,
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*,
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request: RAGAskRequest,
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current_user: Any,
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conversation_context: dict[str, Any] | None,
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tenant_project_context: dict[str, Any] | None,
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) -> PMFlowAgentEnvironmentResult:
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result = PMFlowAgentEnvironmentResult()
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snapshot_step = PMFlowAgentStepPacket(
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step_id=new_pmflow_agent_id("env"),
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index=0,
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kind="environment_snapshot",
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status="completed",
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label="读取环境：建立本轮上下文快照",
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summary="已记录当前空间、会话和客户安全对象锚点。",
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)
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result.steps.append(snapshot_step)
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result.observations.append(
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PMFlowAgentObservationPacket(
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step_id=snapshot_step.step_id,
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source_kind="environment_snapshot",
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summary="已建立客户安全环境快照。",
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confidence="high",
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facts=_environment_facts(
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request=request,
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conversation_context=conversation_context,
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tenant_project_context=tenant_project_context,
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),
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gaps=_environment_gaps(
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request=request,
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conversation_context=conversation_context,
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tenant_project_context=tenant_project_context,
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),
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)
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)
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space_observation = await self._execute_tool(
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tool_name="inspect_space_collections",
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tool_input={"question": str(request.question or "").strip()[:1200]},
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request=request,
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current_user=current_user,
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conversation_context=conversation_context,
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tenant_project_context=tenant_project_context,
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)
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_append_tool_observation(
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result,
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tool_name="inspect_space_collections",
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label="读取环境：检查当前空间集合",
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observation=space_observation,
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)
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project_ref = _strong_project_ref(
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request=request,
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conversation_context=conversation_context,
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tenant_project_context=tenant_project_context,
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)
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if project_ref:
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project_observation = await self._execute_tool(
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tool_name="inspect_project_operating_state",
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tool_input={"project_ref": project_ref},
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request=request,
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current_user=current_user,
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conversation_context=conversation_context,
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tenant_project_context=tenant_project_context,
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)
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_append_tool_observation(
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result,
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tool_name="inspect_project_operating_state",
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label="读取环境：检查项目世界状态",
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observation=project_observation,
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)
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return result
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async def _execute_tool(
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self,
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*,
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tool_name: str,
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tool_input: dict[str, Any],
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request: RAGAskRequest,
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current_user: Any,
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conversation_context: dict[str, Any] | None,
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tenant_project_context: dict[str, Any] | None,
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) -> PMFlowAIAgentObservation:
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return await self.tool_registry.execute(
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proposal=PMFlowAIAgentStepProposal(
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action="tool",
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tool_name=tool_name,
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tool_input=tool_input,
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rationale="Agent OS environment observation",
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expected_observation="customer-safe environment facts",
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confidence="medium",
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),
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request=request,
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workspace=None,
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current_user=current_user,
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conversation_context=conversation_context,
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tenant_project_context=tenant_project_context,
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)
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def _append_tool_observation(
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result: PMFlowAgentEnvironmentResult,
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*,
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tool_name: str,
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label: str,
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observation: PMFlowAIAgentObservation,
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) -> None:
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step = PMFlowAgentStepPacket(
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step_id=new_pmflow_agent_id("env"),
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index=len(result.steps),
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kind="environment_tool",
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status="completed",
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label=label,
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summary=str(getattr(observation, "summary", "") or "")[:600],
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tool_name=tool_name,
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)
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result.steps.append(step)
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result.observations.append(_packet_from_agent_observation(observation, step_id=step.step_id))
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def _packet_from_agent_observation(observation: PMFlowAIAgentObservation, *, step_id: str) -> PMFlowAgentObservationPacket:
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gaps = [
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dict(item)
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for item in list(getattr(observation, "facts", []) or [])
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if isinstance(item, dict) and ("gap" in item.get("type", "") or item.get("user_actionable") is not None)
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][:24]
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return PMFlowAgentObservationPacket(
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observation_id=str(getattr(observation, "observation_id", "") or new_pmflow_agent_id("obs"))[:80],
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step_id=step_id,
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source_kind=str(getattr(observation, "source", "") or "agent_tool")[:80],
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summary=str(getattr(observation, "summary", "") or "")[:800],
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confidence=str(getattr(observation, "confidence", "") or "unknown")[:32],
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facts=[dict(item) for item in list(getattr(observation, "facts", []) or [])[:24] if isinstance(item, dict)],
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gaps=gaps,
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)
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def _environment_facts(
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*,
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request: RAGAskRequest,
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conversation_context: dict[str, Any] | None,
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tenant_project_context: dict[str, Any] | None,
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) -> list[dict[str, Any]]:
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surface = _surface_context(tenant_project_context)
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facts: list[dict[str, Any]] = [
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{"type": "user_goal", "summary": str(request.question or "").strip()[:500]},
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{"type": "surface", "name": str(surface.get("surface") or surface.get("page") or "space")[:80]},
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{"type": "visible_object_count", "count": len(_visible_objects(surface))},
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]
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project_ref = _strong_project_ref(
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request=request,
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conversation_context=conversation_context,
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tenant_project_context=tenant_project_context,
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)
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if project_ref:
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facts.append({"type": "strong_object_anchor", "object_ref": project_ref, "object_type": "project"})
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session_id = (conversation_context or {}).get("session_id")
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if session_id is not None:
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facts.append({"type": "session_anchor", "session_id": session_id})
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return facts
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def _environment_gaps(
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*,
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request: RAGAskRequest,
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conversation_context: dict[str, Any] | None,
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tenant_project_context: dict[str, Any] | None,
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) -> list[dict[str, Any]]:
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if _strong_project_ref(
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request=request,
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conversation_context=conversation_context,
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tenant_project_context=tenant_project_context,
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):
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return []
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return [
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{
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"type": "object_anchor_gap",
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"summary": "本轮没有结构化强项目锚点；Agent OS 不会把可见项目列表自动当作当前项目。",
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"user_actionable": False,
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}
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]
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def _strong_project_ref(
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*,
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request: RAGAskRequest,
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conversation_context: dict[str, Any] | None,
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tenant_project_context: dict[str, Any] | None,
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) -> str | None:
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request_project_id = _safe_int(getattr(request, "project_id", None))
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if request_project_id is not None:
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return f"project:{request_project_id}"
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context_project_id = _safe_int((conversation_context or {}).get("current_project_id"))
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if context_project_id is not None:
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return f"project:{context_project_id}"
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surface = _surface_context(tenant_project_context)
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focus = surface.get("current_focus_object")
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if isinstance(focus, dict):
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object_ref = str(focus.get("object_ref") or "").strip()
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object_type = str(focus.get("object_type") or "").strip()
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object_id = _safe_int(focus.get("object_id"))
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if object_ref.startswith("project:"):
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return object_ref[:160]
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if object_type == "project" and object_id is not None:
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return f"project:{object_id}"
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return None
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def _surface_context(tenant_project_context: dict[str, Any] | None) -> dict[str, Any]:
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context = dict(tenant_project_context or {})
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surface = context.get("surface_context")
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return dict(surface) if isinstance(surface, dict) else {}
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def _visible_objects(surface_context: dict[str, Any]) -> list[dict[str, Any]]:
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rows = surface_context.get("visible_objects")
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return [dict(item) for item in list(rows or []) if isinstance(item, dict)]
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def _safe_int(value: Any) -> int | None:
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try:
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if value is None or value == "":
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return None
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return int(value)
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except Exception:
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return None
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__all__ = ["PMFlowAgentEnvironmentResult", "PMFlowAgentEnvironmentService"]
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