111 lines
4.2 KiB
Python
111 lines
4.2 KiB
Python
"""Renderer selection registry for PMFlow AI turn runtime.
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The registry chooses renderer candidates from canonical TurnState. It does not
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inspect user text and it does not generate answers. Runtime-owned renderer
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functions execute the selected candidates and may later be moved behind the
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same keys without changing the turn loop.
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import Literal
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from ..schemas.pmflow_ai_turn_runtime import PMFlowAITurnState
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from .pmflow_ai_static_contract_registry import PMFlowAIStaticContractRegistry
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RendererKey = Literal[
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"static_contract",
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"collection_snapshot",
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"project_operating_packet",
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"open_judgement",
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"llm_state_compose",
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"safe_fallback",
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]
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@dataclass(frozen=True)
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class PMFlowAIAnswerRendererCandidate:
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renderer_key: RendererKey
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reason: str
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priority: int
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class PMFlowAIAnswerRendererRegistry:
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"""Select deterministic and generative renderer candidates for a turn."""
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def select_candidates(self, turn_state: PMFlowAITurnState) -> list[PMFlowAIAnswerRendererCandidate]:
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candidates: list[PMFlowAIAnswerRendererCandidate] = []
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if PMFlowAIStaticContractRegistry().resolve_for_turn_state(turn_state) is not None:
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candidates.append(
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PMFlowAIAnswerRendererCandidate(
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renderer_key="static_contract",
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reason="权威真源是静态产品合同，优先确定性表达。",
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priority=10,
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)
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)
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if _can_render_collection(turn_state):
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candidates.append(
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PMFlowAIAnswerRendererCandidate(
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renderer_key="collection_snapshot",
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reason="TurnState 已包含集合观察或集合 draft，可确定性展示列表。",
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priority=20,
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)
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)
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if _has_project_operating_packet(turn_state):
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candidates.append(
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PMFlowAIAnswerRendererCandidate(
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renderer_key="project_operating_packet",
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reason="TurnState 已包含项目运行态 packet，可确定性表达项目状态。",
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priority=30,
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)
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)
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if not list(turn_state.evidence_state.known_facts or []):
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candidates.append(
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PMFlowAIAnswerRendererCandidate(
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renderer_key="open_judgement",
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reason="当前没有可吸收 facts，尝试基于开放判断状态给出受控初判。",
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priority=40,
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)
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)
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candidates.extend(
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[
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PMFlowAIAnswerRendererCandidate(
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renderer_key="llm_state_compose",
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reason="使用 TurnState 进行受控合成。",
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priority=90,
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),
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PMFlowAIAnswerRendererCandidate(
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renderer_key="safe_fallback",
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reason="无 renderer 产出时使用客户安全 fallback。",
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priority=100,
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),
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]
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)
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return sorted(candidates, key=lambda item: item.priority)
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def _can_render_collection(turn_state: PMFlowAITurnState) -> bool:
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selected = turn_state.selected_frame
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if selected is not None and selected.operation_kind == "list_collection":
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return True
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if str(turn_state.answer_state.answer_shape or "") == "fact_list":
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return True
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draft = dict(turn_state.customer_packet_draft or {})
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if isinstance(draft.get("items"), list) or isinstance(draft.get("count"), int):
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return True
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return any(
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observation.observation_type == "collection_snapshot"
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and (bool(observation.items) or observation.count is not None)
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for observation in list(turn_state.observations or [])
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)
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def _has_project_operating_packet(turn_state: PMFlowAITurnState) -> bool:
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structured = dict(turn_state.evidence_state.structured_evidence or {})
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if isinstance(structured.get("project_operating_evidence_packet"), dict):
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return True
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packets = structured.get("project_operating_evidence_packets")
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return any(isinstance(packet, dict) for packet in list(packets or []))
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