Land the production + test surface for the Step 17 cascade POPUP terminal (DETERMINISTIC -> POPUP -> AI_REPAIR -> USER_OVERRIDE) per Stage 2 plan R2. u11 (baseline-red invariance gate) was already landed in7c93031ahead of this commit; this commit completes u1~u10 plus the Stage 3 R7 follow-up anchor re-pin for test_imp17_comment_anchor.py. Implementation units (Stage 2 R2 contract): u1 frame_reselect_insufficient failure_type + post-frame remeasure (q4) - src/phase_z2_failure_router.py, src/phase_z2_pipeline.py u2 NEXT_ACTION_BY_FAILURE row + impl_status flip - src/phase_z2_failure_router.py u3 Router details_popup_escalation MISSING->IMPLEMENTED + executor stub - src/phase_z2_router.py u4 step17.py AI split-decision contract (POPUP cascade_stage + route_for_label + skip_reason); API gated - src/phase_z2_ai_fallback/step17.py u5 Step 17 POPUP gate executor; popup_escalation_plan + has_popup marker - src/phase_z2_pipeline.py, src/phase_z2_ai_fallback/step17.py u6 Composition popup binding -- yaml strategy -> zone payload - src/phase_z2_composition.py u7 Pipeline composer -> render_slide wiring (popup_html / preview_text / has_popup) - src/phase_z2_pipeline.py u8 slide_base.html <details>/<summary> popup wrapper - templates/phase_z2/slide_base.html u9 display_strategies.yaml inline_preview + popup metadata - templates/phase_z2/regions/display_strategies.yaml u10 MDX preservation invariant: popup=full source / body=summary or subset (asserted by tests/phase_z2/test_popup_mdx_preservation.py) u11 (already in7c93031) -- baseline-red invariance gate Stage 3 R7 follow-up (anchor re-pin, test-only): - tests/orchestrator_unit/test_imp17_comment_anchor.py Pre-anchor additions in src/phase_z2_pipeline.py (u1 / u5 / u7) shifted the restructure/reject route-hint comments 578/579 -> 586/587. Re-pinned the two guard tests (and docstring re-pin lineage 564 -> 570 -> 578 -> 586). Production code untouched. Verification (Stage 4 R1): pytest -q tests/orchestrator_unit/test_imp17_comment_anchor.py -> 2 passed / 0.02s pytest -q <10 IMP-35 unit files in tests/phase_z2 + tests/phase_z2_ai_fallback> -> 136 passed / 15.94s Baseline-red invariance gate (tests/test_imp47b_step12_ai_wiring.py + tests/test_phase_z2_ai_fallback_config.py) -> 4 failed / 6 passed; FAILED set === IMP35_BASELINE_RED_NODE_IDS (frozen registry from7c93031). Contract holds. Codex Stage 4 R1 = YES (independent verify). Guardrails honored: - MDX content preservation: popup carries full source, body holds summary or subset only (CLAUDE.md 자세히보기 원칙; feedback_phase_z_spacing_direction -- capacity expanded, no margin shrink). - AI isolation contract: Step 17 POPUP gate is deterministic; AI hook surface is split-decision contract only, API call gated. - No hardcoding: escalation thresholds derived from existing overflow detector outputs; preview_chars deterministic from container px. - 1 commit = 1 decision unit: u1~u10 land together as the planned production surface; u11 was deliberately split into7c93031as Stage 3 R7 carve-out, and the R7 anchor re-pin rides with this commit because it is the direct shift consequence of the u1/u5/u7 pre-anchor additions. - Scope-locked: .claude/settings.json explicitly excluded (Stage 4 exit report contract). Out of scope (per Stage 1 + Stage 2): - AI_REPAIR API activation (post IMP-35 axis). - IMP-34 zone resize, IMP-36 responsive fit (chain partners, separate issues). - Print-time auto-expand JavaScript for <details>. - Popup escalation in stages other than Step 17. - Baseline-red body repair (4 frozen failures) -- separate follow-up issue; u11 only guards the count. - frame_reselect algorithm changes (entry point only). - templates/phase_z2/slide_base.html path rename. source_comment_ids: Stage 1: claude_stage1_problem_review_imp35, codex_stage1_verification_imp35_yes Stage 2: Claude #4 R2 plan, Codex #5 R2 YES Stage 3: Claude #86 (R7 anchor re-pin), Codex #87 YES Stage 4: Claude #88 R1, Codex #89 R1 YES Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
309 lines
15 KiB
Python
309 lines
15 KiB
Python
"""Phase Z-2 overflow_router v0 (A2 — 정책 매핑 layer 만).
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fit_classifier 의 출력 (category) 를 spec §4 의 *proposed_action* 으로 매핑하는 layer.
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본 module 은 ***매핑까지만***. 실제 action 실행은 별도 step (A3+).
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출력 = 각 classification 에 proposed_action 추가 + router 전체 summary.
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원칙 :
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- classifier = 사실 분류 (category 결정)
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- router = 정책 결정 (그 category 면 무엇을 *제안* 할 것인가)
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- 본 단계는 *제안 trace* 만. pipeline behavior / abort 정책 / rerender 변경 X
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- 실행 안 됨 → 현재 코드는 여전히 visual_check_passed=False 시 sys.exit(1)
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그러나 debug.json 에 *어떤 action 이 제안됐는지* 가 기록됨
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다음 step (별도 — A3) :
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zone_ratio_retry action 의 *실제 구현* — 지금 spec §4 mapping 의 가장 자주
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트리거되는 action.
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"""
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from __future__ import annotations
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from typing import Optional
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# ─── §4 mapping table (spec PHASE-Z-FIT-CLASSIFIER-ROUTER-SPEC §4) ──
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# category → proposed_action (primary)
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ACTION_BY_CATEGORY: dict[str, str] = {
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"minor_overflow": "zone_ratio_retry",
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"moderate_overflow": "layout_adjust",
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"structural_minor_overflow": "zone_ratio_retry",
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"structural_major_overflow": "details_popup_escalation",
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"tabular_overflow": "details_popup_escalation",
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"frame_capacity_mismatch": "frame_reselect",
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"layout_zone_mismatch": "layout_adjust",
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"hard_visual_fail": "abort",
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}
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# 매핑 근거 — *왜 이 category 면 이 action 인가* trace 용
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ACTION_RATIONALE: dict[str, str] = {
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"minor_overflow":
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"1.5 줄 미만 text/label flow → zone 양보 / spacing 재계산으로 fit 가능",
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"moderate_overflow":
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"1.5~4 줄 text/label → layout/zone ratio 재분배 필요",
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"structural_minor_overflow":
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"structural unit boundary spill (<1 unit drop) → zone 양보로 fit, 단위 자르기 X",
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"structural_major_overflow":
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"1+ structural unit 완전 잘림 → 의미 손실, popup 으로 escalate",
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"tabular_overflow":
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"표는 행 단위로 잘리면 의미 손실 → popup escalate (또는 table-friendly frame reselect)",
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"frame_capacity_mismatch":
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"composition capacity_fit 가 이미 mismatch 신호 → V4 top-k 의 다른 frame 평가",
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"layout_zone_mismatch":
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"frame root 자체 overflow → layout preset 변경 또는 zone 키움",
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"hard_visual_fail":
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"위 매핑 모두 미적용 — 마지막 fallback (현재 코드는 sys.exit 으로 abort)",
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}
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# 각 action 의 *현재 코드* 구현 상태 (2026-04-29 기준; IMP-12 u7 cascade 2026-05-18;
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# IMP-35 u3 popup-stub 2026-05-23)
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# A2 단계에서 이 매핑이 *어디까지 자동 처리되고 어디서 막히는지* trace 확보용
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ACTION_IMPLEMENTATION_STATUS: dict[str, str] = {
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"zone_ratio_retry": "IMPLEMENTED", # A3 (2026-04-29) phase_z2_retry.plan_zone_ratio_retry + pipeline orchestration
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"layout_adjust": "MISSING",
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# IMP-35 (#64) u3 — MISSING → IMPLEMENTED on the primary router surface.
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# `plan_details_popup_escalation` (below) provides the deterministic stub
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# that downstream units consume: u4 binds the AI split-decision contract
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# in `src/phase_z2_ai_fallback/step17.py`; u5 wires the Step 17 POPUP
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# gate executor in `src/phase_z2_pipeline.py`. Router-level mapping is
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# decoupled from orchestrator wiring (same precedent as the IMP-12 u7
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# cascade actions below): IMPLEMENTED here reflects deterministic
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# *surface availability* (importable stub), not whether a given pipeline
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# run has invoked it. The failure_router companion surface
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# (NEXT_ACTION_IMPLEMENTATION_STATUS in phase_z2_failure_router.py) keeps
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# `details_popup_escalation` as MISSING until u5 lands the pipeline gate.
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"details_popup_escalation": "IMPLEMENTED",
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"frame_reselect": "PARTIAL", # IMP-05 pre-render rank-2/3 fallback implemented; post-render rerender trace-only
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"adapter_needed": "PARTIAL", # composition v0.1.1 의 mapper FitError catch
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"abort": "IMPLEMENTED", # sys.exit(1) — pipeline 의 현재 default
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# IMP-12 u7 (2026-05-18): cascade-only salvage actions (no ACTION_BY_CATEGORY row;
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# surfaced via NEXT_ACTION_BY_FAILURE in phase_z2_failure_router). plan/apply pairs
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# implemented in phase_z2_retry; pipeline orchestrator wiring lands in u8/u9.
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"cross_zone_redistribute": "IMPLEMENTED", # u4 phase_z2_retry.plan_cross_zone_redistribute + apply_cross_zone_redistribute_css
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"glue_compression": "IMPLEMENTED", # u5 phase_z2_retry.plan_glue_compression + apply_glue_compression_css
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"font_step_compression": "IMPLEMENTED", # u6 phase_z2_retry.plan_font_step_compression + apply_font_step_compression_css
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}
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# ─── 단일 분류 → routing 결과 ─────────────────────────────────────
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def route_action(category: str) -> dict:
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"""category → proposed_action mapping 결과 (단일).
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Returns:
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dict :
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proposed_action : action 이름 (또는 None)
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rationale : *왜* 이 action 인가
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implementation_status : implemented / partial / missing / unknown
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mapping_source : "spec §4 ACTION_BY_CATEGORY" 또는 "no mapping"
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"""
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action = ACTION_BY_CATEGORY.get(category)
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if action is None:
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return {
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"proposed_action": None,
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"rationale": f"category '{category}' has no mapping in ACTION_BY_CATEGORY",
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"implementation_status": "unknown",
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"mapping_source": "no mapping (unknown category)",
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}
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return {
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"proposed_action": action,
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"rationale": ACTION_RATIONALE.get(category, ""),
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"implementation_status": ACTION_IMPLEMENTATION_STATUS.get(action, "unknown"),
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"mapping_source": "spec §4 ACTION_BY_CATEGORY",
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}
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# ─── fit_classification 전체 → router decision ──────────────────
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def route_fit_classification(fit_classification: dict) -> dict:
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"""fit_classification 의 모든 classifications 에 proposed_action 추가 + summary.
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각 classification 에 다음 필드를 *추가* (기존 필드 보존) :
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- proposed_action
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- proposed_action_rationale
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- proposed_action_implementation_status
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- proposed_action_mapping_source
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Returns:
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router decision summary dict :
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router_active : True/False (visual_check_passed=False 일 때만 True)
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proposed_actions_summary : unique action 들 sorted list
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implementation_status_summary : {status: count} dict
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routed_count : 처리된 classification 수
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routed_details : per-classification routing trace
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missing_actions_pending_impl : 본 routing 에서 *현재 미구현* 인 action 모음
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note : 사용자 안내 텍스트
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"""
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if fit_classification.get("visual_check_passed", True):
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return {
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"router_active": False,
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"proposed_actions_summary": [],
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"implementation_status_summary": {},
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"routed_count": 0,
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"routed_details": [],
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"missing_actions_pending_impl": [],
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"note": "visual check passed — no overflow to route",
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}
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classifications = fit_classification.get("classifications", []) or []
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routed_details = []
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for cls in classifications:
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category = cls.get("category", "hard_visual_fail")
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routing = route_action(category)
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# classification entry 에 proposed_action 정보 *추가* (기존 필드 보존)
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cls["proposed_action"] = routing["proposed_action"]
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cls["proposed_action_rationale"] = routing["rationale"]
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cls["proposed_action_implementation_status"] = routing["implementation_status"]
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cls["proposed_action_mapping_source"] = routing["mapping_source"]
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routed_details.append({
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"source": cls.get("source"),
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"zone_position": cls.get("zone_position"),
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"category": category,
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"proposed_action": routing["proposed_action"],
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"implementation_status": routing["implementation_status"],
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})
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# summary
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actions_seen = sorted({
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r["proposed_action"] for r in routed_details
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if r["proposed_action"] is not None
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})
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status_breakdown: dict[str, int] = {}
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missing_actions: list[str] = []
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for r in routed_details:
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s = r["implementation_status"]
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status_breakdown[s] = status_breakdown.get(s, 0) + 1
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if s == "MISSING" and r["proposed_action"] not in missing_actions:
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missing_actions.append(r["proposed_action"])
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return {
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"router_active": True,
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"proposed_actions_summary": actions_seen,
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"implementation_status_summary": status_breakdown,
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"routed_count": len(routed_details),
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"routed_details": routed_details,
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"missing_actions_pending_impl": sorted(missing_actions),
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"note": (
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"router 는 category → proposed_action 매핑까지 담당. 실제 action 실행은 "
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"pipeline 의 별도 orchestrator 가 처리 (예: zone_ratio_retry 는 "
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"_attempt_zone_ratio_retry 에서 실행). proposed_action 의 implementation_status "
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"가 IMPLEMENTED 이면 pipeline 이 시도하고 결과는 retry_trace 에 기록, "
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"MISSING 이면 그 action 은 실행 X 이고 기존 abort/status 흐름 (sys.exit(1)) 으로 종료."
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),
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}
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# ─── IMP-35 (#64) u3 — details_popup_escalation deterministic stub ─
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# Surface contract for the cascade-terminal popup escalation. This stub
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# does NOT mutate HTML / CSS / MDX content; it emits the canonical plan
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# marker that the Step 17 POPUP gate (u5) and the AI split-decision hook
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# (u4) consume. Keeping the executor surface here (next to the primary
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# ACTION_BY_CATEGORY mapping) lets the router report IMPLEMENTED for
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# `details_popup_escalation` while u4/u5 are still landing.
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#
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# Contract (locked in Stage 2 IMPLEMENTATION_UNITS u3):
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# - Inputs: classification dict (a single fit_classifier output row).
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# The category MUST be one of the two ACTION_BY_CATEGORY
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# rows that map onto `details_popup_escalation` —
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# `structural_major_overflow` or `tabular_overflow`.
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# Other categories raise the stub's defensive guard (so
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# callers do not silently popup-escalate the wrong category).
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# - Output: popup_escalation_plan dict with `feasible=True`,
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# `stub=True`, the source category, the canonical
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# ACTION_RATIONALE entry, and `needs_split_decision=True`
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# to flag that u4 (AI hook) must run before u5 renders.
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# - No side effects (no AI call, no MDX read, no HTML mutation).
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#
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# Guardrails honored:
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# - feedback_ai_isolation_contract: stub is deterministic-with-data;
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# no AI call inside the router surface.
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# - Phase Z spacing 방향: stub does not shrink common margins; it
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# expands capacity by routing content to popup downstream.
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# - 자세히보기 원칙 (CLAUDE.md): plan carries the marker that u5 uses
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# to put MDX 원문 in popup body and a summary/subset in preview.
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# - 1 turn = 1 unit: this is router-surface only. u4/u5 own the
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# downstream wiring on their respective files.
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# Categories that legitimately escalate onto details_popup_escalation
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# per the ACTION_BY_CATEGORY mapping above. Kept as a derived constant
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# so the router cannot drift away from the single source of truth.
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POPUP_ESCALATION_CATEGORIES: frozenset[str] = frozenset(
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category
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for category, action in ACTION_BY_CATEGORY.items()
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if action == "details_popup_escalation"
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)
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def plan_details_popup_escalation(classification: dict) -> dict:
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"""Cascade-terminal popup escalation plan stub (IMP-35 u3).
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Returns a deterministic popup_escalation_plan marker. The actual
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content split (popup_html / preview_text / has_popup payload) is
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composed downstream: u4 binds the AI split-decision contract on
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`src/phase_z2_ai_fallback/step17.py`; u5 wires the Step 17 POPUP
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gate executor on `src/phase_z2_pipeline.py`.
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Args:
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classification: a single fit_classifier classification dict.
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Must contain a `category` key. Only the categories that
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map onto `details_popup_escalation` in ACTION_BY_CATEGORY
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(currently `structural_major_overflow` and `tabular_overflow`)
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are accepted; any other category produces an
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`feasible=False` plan with `failure_reason` so the caller
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never silently popup-escalates the wrong overflow shape.
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Returns:
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popup_escalation_plan dict with at least:
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action : "details_popup_escalation"
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feasible : True/False (True for accepted categories)
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stub : True (marks u3 surface; u4/u5 fill in)
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category : echoed from input
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rationale : canonical ACTION_RATIONALE entry
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needs_split_decision : True (u4 AI hook must run before u5 renders)
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mapping_source : "IMP-35 u3 plan_details_popup_escalation stub"
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note : downstream-wiring pointer text
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"""
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category = (classification or {}).get("category")
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base = {
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"action": "details_popup_escalation",
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"stub": True,
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"category": category,
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"mapping_source": "IMP-35 u3 plan_details_popup_escalation stub",
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}
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if category not in POPUP_ESCALATION_CATEGORIES:
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return {
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**base,
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"feasible": False,
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"needs_split_decision": False,
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"rationale": "",
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"failure_reason": (
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f"category {category!r} does not map onto details_popup_escalation "
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f"in ACTION_BY_CATEGORY. Accepted categories: "
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f"{sorted(POPUP_ESCALATION_CATEGORIES)}. Defensive guard — "
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f"router must not silently popup-escalate the wrong overflow shape."
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),
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"note": (
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"u3 stub — caller passed a category that should not popup-escalate. "
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"Honour the ACTION_BY_CATEGORY mapping at the router entry point."
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),
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}
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return {
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**base,
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"feasible": True,
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"needs_split_decision": True,
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"rationale": ACTION_RATIONALE.get(category, ""),
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"note": (
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"u3 stub — actual content split planning lands in u4 "
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"(AI split-decision contract on src/phase_z2_ai_fallback/step17.py) "
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"and u5 (Step 17 POPUP gate executor on src/phase_z2_pipeline.py). "
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"popup body = MDX 원문, preview = summary/subset (자세히보기 원칙)."
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),
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}
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