2026-09-29 20:38:02 +08:00
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"""T07-c 预审运行装配：把冻结方案、结论校验与专项配置收成一条可审计的运行记录。
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依据：docs/v2/03-detailed-design.md §9.2/§9.3、02-architecture.md §4；
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BR-13/14/20/31、AC-13/14/45。
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**这是既有 run 对象的受约束投影，不是第二份运行存储。** 既有
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`ProjectAssistantService.enqueue()` 已经提供输入快照冻结、幂等键、revision 冲突与
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队列恢复（AC-13/AC-14 的实现），本模块**不重做**这些，只负责：
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1. 把冻结方案与专项配置投影进 ScreeningRun 并校验
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2. 把政策结论、降级与维度状态落成契约合法的运行视图
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3. 保证任何路径都写不出未校准概率
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"""
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from __future__ import annotations
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from contracts.prescreen import (
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DataDomain,
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DimensionResult,
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2026-09-30 12:34:45 +08:00
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DimensionSpec,
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ErrorCode,
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2026-09-29 20:38:02 +08:00
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ProbabilityView,
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ScreeningRun,
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)
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from services import assistant_store as store
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from services import prescreen_policy as policy
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def versions_block(frozen_plan: dict, extra: dict | None = None) -> dict:
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"""冻结的运行版本块。缺哪一项就明确留空，不编造版本号。"""
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plan = frozen_plan.get("plan") or {}
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components = frozen_plan.get("component_versions") or [
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{"id": item["id"], "version": item.get("version")}
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for item in [plan] + list(frozen_plan.get("skills") or ())
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+ list(frozen_plan.get("rules") or ())
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+ ([frozen_plan["template"]] if frozen_plan.get("template") else [])
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]
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block = {
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"schema": 1,
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"policy": "prescreen_policy@1",
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"skills": [item for item in components if item.get("id")],
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"experiences": list(frozen_plan.get("experience_versions") or ()),
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"model": None, # 主审模型配置由运行冻结，未配置即留空
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"questions": None, # 题库版本在 T08 统一适配后填入，P0 留空
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"plan": {"id": plan.get("id"), "version": plan.get("version")},
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"plan_hash": frozen_plan.get("content_hash"),
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}
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block.update(extra or {})
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return block
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def dimension_results(frozen_plan: dict, findings) -> list[dict]:
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"""把维度与本次核查结果对上：命中即 checked，缺证即 unknown，永不默认成立。"""
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result_by_code = {}
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for item in findings or ():
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result_by_code.setdefault(str(item.get("code")), []).append(item)
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rows = []
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for spec in frozen_plan.get("dimensions") or ():
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refs = spec.get("component_refs") or ()
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bases, states, reported = [], set(), 0
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for ref in refs:
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items = result_by_code.get(str(ref.get("id")), ())
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if not items:
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continue # 该组件本次没有任何结果 = 未报告
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reported += 1
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for item in items:
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states.add(item.get("result"))
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bases.extend(item.get("evidence_ids") or [])
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unreported = len(refs) - reported
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if states & {"issue"}:
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state = "blocked"
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elif unreported or not states or (states & {"unknown", "error", "not_applicable"}):
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state = "unknown"
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else:
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state = "checked"
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stages = [item.get("stage") for ref in refs
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for item in result_by_code.get(str(ref.get("id")), ())
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if isinstance(item.get("stage"), int)]
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rows.append({"id": spec["id"], "state": state,
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"stage": max(stages) if stages else None,
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"basis_ids": sorted(set(bases))})
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return rows
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def probability_view(snapshot_id: str, as_of: str | None = None,
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demo_estimate: dict | None = None) -> dict:
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"""概率视图。真实估计恒为空；演示值只能走 demo_estimate 且必须带说明。"""
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return ProbabilityView(snapshot_id=snapshot_id, as_of=as_of or store.now(),
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demo_estimate=demo_estimate).model_dump(mode="json")
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def assemble(run_body: dict, frozen_plan: dict, decision: dict, judgment_config,
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data_domain: str = "demo", status: str = "completed",
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trajectory_id: str | None = None) -> dict:
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"""装配 ScreeningRun 视图并校验。
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任何一条路径写不出未校准概率：`probability` 与 `probability_view.real_estimate`
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都是契约里的 `None` 类型，传别的值会直接被 pydantic 拒绝。
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"""
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plan = frozen_plan.get("plan") or {}
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snapshot_id = run_body.get("input_snapshot_id") or run_body.get("snapshot_id")
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if not snapshot_id:
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raise ValueError("运行缺少输入快照，无法装配预审视图")
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body = {
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"id": run_body["id"],
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"project_id": run_body["project_id"],
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"data_domain": data_domain,
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"revision": run_body.get("revision", 1),
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"snapshot_id": snapshot_id,
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"plan_ref": {"id": plan.get("id", ""), "version": str(plan.get("version", ""))},
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"status": status,
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"recommendation": decision.get("recommendation"),
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"findings": decision.get("findings") or [],
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"missing_inputs": decision.get("missing_inputs") or [],
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"applied_experiences": run_body.get("experience_applications") or [],
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"degradations": decision.get("degradations") or [],
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"judgment_config": judgment_config.model_dump(mode="json")
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if hasattr(judgment_config, "model_dump") else dict(judgment_config),
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"versions": versions_block(frozen_plan, {"trajectory_id": trajectory_id}
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if trajectory_id else None),
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"dimension_results": dimension_results(frozen_plan, decision.get("findings")),
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"evidence": [dict(item) for item in (run_body.get("evidence") or ())][:200],
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"run_instruction": run_body.get("requirement") or "",
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"created_at": run_body.get("created_at") or store.now(),
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"finished_at": run_body.get("ended_at"),
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}
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if status in ("completed", "partial"):
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body["probability_view"] = probability_view(snapshot_id)
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result = ScreeningRun(**body).model_dump(mode="json")
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if result["probability"] is not None:
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raise ValueError("未校准时不得产出审批概率")
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if (result.get("probability_view") or {}).get("real_estimate") is not None:
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raise ValueError("P0 的真实概率估计必须为空")
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return result
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def assert_versions_frozen(screening: dict) -> None:
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"""运行必须冻结方案与专项配置，否则不得进入执行（BR-13 / BR-20）。"""
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reference = screening.get("plan_ref") or {}
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if not reference.get("id") or not reference.get("version"):
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raise ValueError("运行未冻结评审方案版本，不得执行")
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config = screening.get("judgment_config") or {}
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if config.get("enabled") and (not config.get("profile_id")
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or config.get("profile_revision") is None):
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raise ValueError("启用专项的运行必须冻结配置 ID 与修订")
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2026-09-30 12:34:45 +08:00
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# 证据成熟度刻度。**只表达证据成熟度，不看结论好坏**：发现问题不会降阶段，
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STAGE_SCALE_ID = "evidence-stage"
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STAGE_SCALE_VERSION = "1.0.0"
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STAGE_LEVELS = [
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{"value": 0, "label": "未提供", "criterion": "本次没有该核查项的结果"},
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{"value": 1, "label": "仅有说明", "criterion": "有结论但未引用任何证据"},
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{"value": 2, "label": "资料待核", "criterion": "引用了证据；尚无交叉核验记录"},
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{"value": 3, "label": "交叉核验", "criterion": "有核验记录证明证据之间互相印证"},
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{"value": 4, "label": "人工复核", "criterion": "有人工复核记录"},
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]
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DISABLED_JUDGMENT_CONFIG = {
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"enabled": False, "provider": "disabled",
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"disabled_reason": "本次运行未启用专项判断；主审仍按规则、工具与经验形成意见",
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}
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# 阶段 3/4 需要"核验记录"或"人工复核记录"这类依据，P0 的执行链还产不出，
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def stage_from_check(item) -> int:
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"""核查项 → 证据成熟度阶段（BR-46）。"""
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if item.get("result") in (None, "not_applicable", "error"):
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return 0
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return 2 if item.get("evidence_ids") else 1
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def _component_of(step, skills, rules):
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"""步骤归属的组件：**必须是冻结方案里声明过的技能或规则**。
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既有执行器把技能、规则、经验核查都落成 step，其中经验核查这类不在方案里的
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步骤不是核查维度；反过来方案声明的组件若本次没执行，也不会出现在结果里
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（维度的定义是"跑了什么"，不是"方案里写了什么"）。
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"""
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step_id = str(step.get("step_id") or "")
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skill_id = str((step.get("skill") or {}).get("id") or "")
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lookup = skill_id or step_id
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if not lookup or lookup != step_id:
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return None
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item = next((s for s in skills or () if s.get("id") == lookup), None)
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if item is None:
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item = next((r for r in rules or () if r.get("id") == lookup), None)
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if item is None:
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return None
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return lookup, str(item.get("name") or lookup), str(item.get("version") or "1.0.0")
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def dimensions_and_evidence(steps, skills, rules):
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"""本次实际执行的组件 → 维度定义 + 用于判定状态与阶段的核查输入（BR-46）。
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只投影真实执行记录：步骤状态决定该维度是否算已核查，核查项决定是否阻断；
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技能/规则跑通但没有产出核查项时，维度按"已核查"成立——这不等于通过审批。
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方案没有执行记录就不产生维度，绝不补占位轴。
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"""
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dimensions, items, order = [], [], 0
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for step in steps or ():
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component = _component_of(step, skills, rules)
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if not component:
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continue
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component_id, label, version = component
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findings = [dict(item) for item in step.get("findings") or ()]
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codes = [str(item.get("code")) for item in findings if item.get("code")]
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status = str(step.get("status") or "")
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if status == "failed":
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step_result = "error"
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elif status in ("partial", "running", "queued"):
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step_result = "unknown"
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elif any(item.get("result") not in ("pass", "not_applicable") for item in findings):
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step_result = "issue"
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else:
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step_result = "pass"
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evidence_ids = sorted({str(e) for item in findings for e in (item.get("evidence_ids") or ())})
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refs = [{"id": component_id, "version": version}] + [
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{"id": code, "version": version} for code in codes]
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dimensions.append(DimensionSpec(
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id=component_id, label=label, order=order, scale_id=STAGE_SCALE_ID,
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scale_version=STAGE_SCALE_VERSION, levels=STAGE_LEVELS,
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component_refs=refs).model_dump(mode="json"))
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order += 1
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step_item = {"code": component_id, "result": step_result,
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"evidence_ids": evidence_ids, "stage": None}
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step_item["stage"] = stage_from_check(step_item)
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items.append(step_item)
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for finding, code in zip(findings, codes):
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row = {"code": code, "result": finding.get("result"),
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"evidence_ids": list(finding.get("evidence_ids") or ())}
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row["stage"] = stage_from_check(row)
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items.append(row)
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return dimensions, items
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def _degradations(steps, run) -> list[dict]:
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"""失败步骤与运行级失败都留痕，并给出可定位的原因（AC-48）。"""
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rows = []
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for step in steps or ():
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if step.get("status") != "failed":
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continue
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error = (step.get("errors") or [{}])[0]
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kind = str(error.get("type") or "")
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code = (ErrorCode.RUN_BUDGET_EXCEEDED if kind == "TimeoutError"
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else ErrorCode.RUN_STEP_FAILED)
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label = str(step.get("name") or step.get("step_id") or "未命名步骤")
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detail = str(error.get("message") or "步骤未完成")
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rows.append({"code": code, "message": f"{label}：{detail[:400]}"})
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if run.get("status") == "failed" and not rows:
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rows.append({"code": ErrorCode.RUN_STEP_FAILED,
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"message": str(run.get("error") or "运行未完成")[:400]})
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return rows
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def _missing_inputs(steps, run) -> list[str]:
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"""缺证项汇总：来自各步骤与数据错误，去重后保持顺序。"""
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|
|
raw = [str(item) for step in steps or () for item in (step.get("missing_inputs") or ())]
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for item in run.get("data_errors") or ():
|
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|
|
raw.append(str(item.get("message") if isinstance(item, dict) else item))
|
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|
seen, rows = set(), []
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|
for item in raw:
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if item and item not in seen:
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|
seen.add(item)
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|
rows.append(item[:200])
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return rows
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|
|
def screening_from_run(run: dict, data_domain: str = "demo",
|
|
|
|
|
|
judgment_config=None) -> dict:
|
|
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|
|
|
"""把**一次真实运行的执行结果**装配成新版预审视图（AC-46/47/48/49）。
|
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|
|
|
|
|
|
|
|
|
|
这是执行链的出口：由 worker 在运行结束时调用，因此正常发起评审就会产生记录，
|
|
|
|
|
|
不需要测试或演示脚本注入（BR-45）。方案取自运行创建时冻结的 components，
|
|
|
|
|
|
不在装配时重读目录，避免"跑的是旧版本、显示的是新版本"。
|
|
|
|
|
|
"""
|
|
|
|
|
|
components = run.get("components") or {}
|
|
|
|
|
|
checks = [dict(item) for item in run.get("checks") or ()]
|
|
|
|
|
|
steps = list(run.get("steps") or ())
|
|
|
|
|
|
skills = list(components.get("skills") or ())
|
|
|
|
|
|
rules = list(components.get("rules") or ())
|
|
|
|
|
|
dimensions, dimension_inputs = dimensions_and_evidence(steps, skills, rules)
|
|
|
|
|
|
frozen_plan = {
|
|
|
|
|
|
"plan": components.get("plan") or {},
|
|
|
|
|
|
"skills": skills,
|
|
|
|
|
|
"rules": rules,
|
|
|
|
|
|
"template": components.get("template") or {},
|
|
|
|
|
|
"content_hash": components.get("content_hash"),
|
|
|
|
|
|
"dimensions": dimensions,
|
|
|
|
|
|
}
|
2026-10-01 13:38:03 +08:00
|
|
|
|
hard_codes = [c['code'] for rule in rules if rule.get('effect') == 'hard' and rule.get('on_match', 'block') == 'block' for c in rule.get('conditions', []) if c.get('code')]
|
|
|
|
|
|
critical = components.get('plan', {}).get('critical_check_ids', [])
|
|
|
|
|
|
decision = policy.decide(checks, _missing_inputs(steps, run), _degradations(steps, run),
|
|
|
|
|
|
critical_check_ids=critical, hard_rule_codes=hard_codes,
|
|
|
|
|
|
rule_versions=[{'id': r['id'], 'version': r['version']} for r in rules])
|
2026-09-30 12:34:45 +08:00
|
|
|
|
decision["findings"] = [dict(item) for item in run.get("findings") or ()]
|
|
|
|
|
|
view = assemble(run, frozen_plan, decision,
|
|
|
|
|
|
judgment_config or DISABLED_JUDGMENT_CONFIG,
|
|
|
|
|
|
data_domain=data_domain,
|
|
|
|
|
|
status=str(run.get("status") or "completed"),
|
|
|
|
|
|
trajectory_id=run.get("id"))
|
|
|
|
|
|
view["dimension_results"] = dimension_results(frozen_plan, dimension_inputs)
|
|
|
|
|
|
return ScreeningRun(**view).model_dump(mode="json")
|
