feat(upstream): merge a6f47abd engine, MCP, and orchestrator
Three-way-merge calculation modules and pl9-export into the product fork while keeping commercial API routes, Raman ayanamsa, and the consultation contract as a keypath superset. Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
Jesse_Chen
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"""Shared report-pack contract normalizer.
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This module intentionally stays thin: it does not compute astrology results and
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does not adjudicate pack truth. It converts existing pack-shaped dictionaries
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into one stable envelope that the final PL9-style renderer can consume.
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"""
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from __future__ import annotations
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from collections.abc import Mapping
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from typing import Any
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try:
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from canonical_jyotish_profile import (
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build_canonical_jyotish_profile,
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build_disputed_method_policy,
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build_reader_engine_boundary_notice,
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)
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except Exception: # pragma: no cover - research helpers are not vendored here
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try:
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from scripts.canonical_jyotish_profile import (
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build_canonical_jyotish_profile,
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build_disputed_method_policy,
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build_reader_engine_boundary_notice,
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)
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except Exception:
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def build_canonical_jyotish_profile():
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return {"profile_id": "product_canonical", "status": "local_fallback"}
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def build_disputed_method_policy():
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return {}
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def build_reader_engine_boundary_notice():
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return {"status": "local_fallback"}
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try:
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from profile_aware_benchmark_boundary_dashboard import load_dashboard_payload
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except Exception: # pragma: no cover - research helpers are not vendored here
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try:
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from scripts.profile_aware_benchmark_boundary_dashboard import load_dashboard_payload
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except Exception:
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def load_dashboard_payload():
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return {"status": "blocked", "reason": "profile_aware_dashboard_absent"}
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SCHEMA = "pl9.unified_report_pack_contract.v1"
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def normalize_report_pack_contract(pack: Mapping[str, Any], *, pack_id: str) -> dict[str, Any]:
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"""Return a uniform report-ready envelope for an existing pack."""
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report_sections = _normalize_report_sections(pack.get("report_sections"))
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audit = _normalize_audit(pack)
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pl9_pages = _as_list(pack.get("pl9_pages") or audit.get("pl9_pages"))
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blocked_reasons = _blocked_reasons(pack, report_sections)
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contract = {
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"schema": SCHEMA,
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"pack_id": pack_id,
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"source_schema": pack.get("schema"),
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"status": _status(pack, audit),
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"profile": dict(pack.get("profile") or {}),
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"pl9_pages": pl9_pages,
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"summary": dict(pack.get("summary") or {}),
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"canonical_jyotish_profile": dict(pack.get("canonical_jyotish_profile") or build_canonical_jyotish_profile()),
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"reader_engine_boundary_notice": dict(
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pack.get("reader_engine_boundary_notice") or build_reader_engine_boundary_notice()
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),
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"multi_engine_difference_notice": _multi_engine_difference_notice(pack),
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"profile_aware_dashboard": dict(pack.get("profile_aware_dashboard") or load_dashboard_payload()),
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"raw_data": _raw_data(pack),
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"normalized_data": _normalized_data(pack),
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"report_sections": report_sections,
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"exports": _normalize_exports(pack.get("exports")),
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"audit": audit,
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"blocked_reasons": blocked_reasons,
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"contract_audit": {
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"missing_fields": _missing_fields(report_sections),
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"source_pack_keys": list(pack.keys()),
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"normalization_boundary": "contract_only_no_astrological_recalculation",
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},
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}
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return contract
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def _status(pack: Mapping[str, Any], audit: Mapping[str, Any]) -> str:
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explicit = pack.get("status") or audit.get("status")
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if explicit:
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return str(explicit)
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statuses: list[str] = []
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report_sections = pack.get("report_sections") if isinstance(pack.get("report_sections"), Mapping) else {}
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for key in ("executive_summary", "thematic_narrative", "evidence_appendix", "pdf_sections"):
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section = report_sections.get(key)
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if isinstance(section, Mapping) and section.get("status"):
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statuses.append(str(section.get("status")))
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for key, value in pack.items():
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if key in {"schema", "profile", "pl9_pages", "summary", "report_sections", "exports", "audit"}:
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continue
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if isinstance(value, Mapping) and value.get("status"):
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statuses.append(str(value.get("status")))
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if not statuses:
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return "blocked"
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if any(status in {"conflict", "parameter_sensitive"} for status in statuses):
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return "parameter_sensitive"
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if any(status in {"partial_verified", "verified"} for status in statuses):
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return "partial_verified"
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if any(status == "not_applicable" for status in statuses):
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return "not_applicable"
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return "blocked"
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def _normalize_report_sections(value: Any) -> dict[str, Any]:
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sections = dict(value or {}) if isinstance(value, Mapping) else {}
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executive = sections.get("executive_summary")
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thematic = sections.get("thematic_narrative")
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evidence = sections.get("evidence_appendix")
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pdf_sections = sections.get("pdf_sections")
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if isinstance(executive, Mapping):
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executive = [str(executive.get("headline") or executive.get("status") or "")]
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elif isinstance(executive, str):
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executive = [executive]
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elif executive is None:
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executive = []
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else:
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executive = list(executive)
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if thematic is None:
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thematic = sections.get("trigger_seed_narrative") or []
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if evidence is None:
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evidence = []
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for key in ("visual_chart_audit", "audit_appendix"):
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if key in sections:
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evidence.append(sections[key])
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return {
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"executive_summary": executive,
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"thematic_narrative": list(thematic) if isinstance(thematic, list) else _as_list(thematic),
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"evidence_appendix": list(evidence) if isinstance(evidence, list) else _as_list(evidence),
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"pdf_sections": list(pdf_sections) if isinstance(pdf_sections, list) else _as_list(pdf_sections),
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}
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def _normalize_exports(value: Any) -> dict[str, Any]:
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exports = dict(value or {}) if isinstance(value, Mapping) else {}
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return {
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"json": exports.get("json"),
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"markdown": exports.get("markdown"),
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"pdf_sections": exports.get("pdf_sections"),
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"ai_evidence_bundle": dict(exports.get("ai_evidence_bundle") or {}),
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}
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def _multi_engine_difference_notice(pack: Mapping[str, Any]) -> dict[str, Any]:
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if isinstance(pack.get("multi_engine_difference_notice"), Mapping):
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return dict(pack["multi_engine_difference_notice"])
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policy = build_disputed_method_policy()
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lanes = []
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for lane_id, lane in policy.items():
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lanes.append(
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{
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"lane_id": lane_id,
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"canonical_standard": lane["canonical_standard"],
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"external_difference_display": "external_observation_conflict",
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"report_assertion_ceiling": lane["report_assertion_ceiling"],
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"reader_text_zh": (
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f"{lane_id} 主口径按 {lane['canonical_standard']}；"
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"其他引擎若不同，会显示为外部观察冲突，不直接改写主结论。"
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),
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}
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)
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return {
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"status": "active",
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"purpose": "reader_safe_multi_engine_difference_display",
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"canonical_profile_id": build_canonical_jyotish_profile()["profile_id"],
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"lanes": lanes,
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"must_not_claim": [
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"external_engine_conflict_overrides_canonical_result",
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"internal_consistency_is_global_truth_closure",
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],
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}
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def _normalize_audit(pack: Mapping[str, Any]) -> dict[str, Any]:
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audit = dict(pack.get("audit") or {})
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must_not_claim = list(audit.get("must_not_claim") or [])
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sections = pack.get("report_sections") if isinstance(pack.get("report_sections"), Mapping) else {}
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for key in ("visual_chart_audit", "evidence_audit"):
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section = sections.get(key) if isinstance(sections, Mapping) else None
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if isinstance(section, Mapping):
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must_not_claim.extend(item for item in section.get("must_not_claim") or [] if item not in must_not_claim)
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if must_not_claim:
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audit["must_not_claim"] = must_not_claim
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return audit
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def _blocked_reasons(pack: Mapping[str, Any], report_sections: Mapping[str, Any]) -> list[str]:
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reasons: list[str] = []
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for key in ("blocked_reasons", "blocked_fields"):
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reasons.extend(str(item) for item in pack.get(key) or [])
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original_sections = pack.get("report_sections") if isinstance(pack.get("report_sections"), Mapping) else {}
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executive = original_sections.get("executive_summary") if isinstance(original_sections, Mapping) else None
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if isinstance(executive, Mapping):
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reasons.extend(str(item) for item in executive.get("blocked_fields") or [])
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if not reasons and _status(pack, pack.get("audit") or {}) == "blocked":
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for item in report_sections.get("evidence_appendix") or []:
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if isinstance(item, str):
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reasons.append(item)
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return list(dict.fromkeys(reasons))
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def _raw_data(pack: Mapping[str, Any]) -> dict[str, Any]:
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return {
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key: value
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for key, value in pack.items()
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if key
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not in {
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"schema",
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"status",
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"profile",
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"pl9_pages",
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"summary",
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"report_sections",
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"exports",
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"audit",
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"profile_aware_dashboard",
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}
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}
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def _normalized_data(pack: Mapping[str, Any]) -> dict[str, Any]:
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return {
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"source_schema": pack.get("schema"),
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"status": pack.get("status") or (pack.get("audit") or {}).get("status") if isinstance(pack.get("audit"), Mapping) else pack.get("status"),
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}
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def _missing_fields(report_sections: Mapping[str, Any]) -> list[str]:
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missing = []
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for key in ("executive_summary", "thematic_narrative", "evidence_appendix"):
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if not report_sections.get(key):
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missing.append(key)
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return missing
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def _as_list(value: Any) -> list[Any]:
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if value is None:
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return []
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if isinstance(value, list):
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return value
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if isinstance(value, tuple):
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return list(value)
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return [value]
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