#!/usr/bin/env python3 """Evidence-backed topic discovery for ordinary users. This layer does not calculate astrology. It ranks existing full-reading evidence into a small set of next topics a user can tap or ask about. """ from __future__ import annotations from typing import Any def _as_dict(value: Any) -> dict[str, Any]: return value if isinstance(value, dict) else {} def _as_list(value: Any) -> list[Any]: return value if isinstance(value, list) else [] def _current_dasha(modules: dict[str, Any]) -> tuple[str | None, str | None, str | None, str | None]: dasha = _as_dict(modules.get("dasha")) current = _as_dict(dasha.get("current_dasha")) antar = _as_dict(current.get("antardasha")) return current.get("lord"), antar.get("lord"), current.get("start"), current.get("end") def _convergence_for(modules: dict[str, Any], *tokens: str) -> dict[str, Any]: convergence = _as_dict(modules.get("dasa_convergence")) activations = _as_dict(convergence.get("domain_activations")) for domain, row in activations.items(): if any(token in str(domain).lower() for token in tokens): found = dict(_as_dict(row)) found.setdefault("domain", domain) return found for row in _as_list(convergence.get("top_convergent_domains")): if isinstance(row, dict) and any(token in str(row.get("domain", "")).lower() for token in tokens): return row if isinstance(row, (list, tuple)) and row and any(token in str(row[0]).lower() for token in tokens): return {"domain": row[0], "convergence_level": row[1] if len(row) > 1 else None} return {} def _vedastro_snapshot(modules: dict[str, Any], domain: str) -> dict[str, Any]: overview = _as_dict(modules.get("vedastro_range_scan_result")) metadata = _as_dict(overview.get("source_metadata")) counts = _as_dict(metadata.get("domain_event_counts")) statuses = _as_dict(metadata.get("domain_statuses")) top = _as_dict(overview.get("top_events_by_domain")).get(domain) status = statuses.get(domain) or overview.get("status") event_count = int(counts.get(domain) or 0) if status == "ok" or event_count: return { "status": "used", "domain": domain, "event_count": event_count, "top_event": top if isinstance(top, dict) else None, "source": "modules.vedastro_range_scan_result", } return { "status": "blocked" if overview else "not_available", "domain": domain, "event_count": event_count, "top_event": None, "source": "modules.vedastro_range_scan_result", } def _evidence_line(label: str, value: Any) -> dict[str, str]: return {"label": label, "value": str(value)} def _strict_contracts(report: dict[str, Any], modules: dict[str, Any]) -> dict[str, Any]: snapshot = _as_dict(_as_dict(_as_dict(report.get("ai_prompt_pack")).get("evidence_snapshot"))) contracts = _as_dict(snapshot.get("strict_workflow_contracts")) if contracts: return contracts mapping = { "career": "career_strict_evidence", "relationship": "relationship_strict_evidence", "finance": "finance_strict_evidence", } compact: dict[str, Any] = {} for route, key in mapping.items(): strict = _as_dict(modules.get(key)) if strict: compact[route] = strict return compact def _topic_audit_gate(contracts: dict[str, Any], route: str) -> dict[str, Any]: contract = _as_dict(contracts.get(route)) bundle = _as_dict(contract.get("strict_adjudication_bundle")) summary = _as_dict(bundle.get("strict_audit_gate")) or _as_dict(contract.get("technique_audit_summary")) if summary: return summary return { "functional_benefic_malefic": {"gate": "hard", "used": False, "status": "blocked"}, "relevant_vargas": {"gate": "hard", "required_keys": [], "present_keys": []}, "vimshottari_narayana_crosscheck": { "gate": "hard", "used": False, "required_timing_systems": ["Vimshottari", "Narayana"], }, "source_priority_boundary": { "gate": "boundary", "official": {}, "local": {}, "fallback_used": [], "blocked_items": [], "conflicts": [], }, } def _topic( *, topic_id: str, title: str, reality_value: str, why: str, evidence: list[dict[str, str]], confidence: str, vedastro: dict[str, Any], strict_audit_gate: dict[str, Any], monthly_adjudication_summary: dict[str, Any], official_day_signal_summary: dict[str, Any], questions: list[str], answer_mode: str = "tap_or_ask", priority: int = 50, ) -> dict[str, Any]: return { "id": topic_id, "title": title, "reality_value": reality_value, "why_worth_exploring": why, "evidence": evidence, "confidence": confidence, "vedastro": vedastro, "strict_adjudication_bundle": { "strict_audit_gate": strict_audit_gate, "monthly_adjudication_summary": monthly_adjudication_summary, "official_day_signal_summary": official_day_signal_summary, }, "strict_audit_gate": strict_audit_gate, "monthly_adjudication_summary": monthly_adjudication_summary, "official_day_signal_summary": official_day_signal_summary, "suggested_questions": questions, "answer_mode": answer_mode, "priority": priority, } def _topic_official_day_signal_summary(contracts: dict[str, Any], modules: dict[str, Any], route: str) -> dict[str, Any]: contract = _as_dict(contracts.get(route)) bundle = _as_dict(contract.get("strict_adjudication_bundle")) summary = _as_dict(bundle.get("official_day_signal_summary")) or _as_dict(contract.get("official_day_signal_summary")) if summary: return summary mapping = { "career": "career_strict_evidence", "relationship": "relationship_strict_evidence", "finance": "finance_strict_evidence", } strict = _as_dict(modules.get(mapping.get(route, ""))) present = _as_dict(strict.get("present_evidence")) external = _as_dict(present.get("external_activation")) signals = _as_list(external.get("official_day_signals")) return { "available": bool(signals), "signal_count": len(signals), "top_day": _as_dict(signals[0]) if signals else None, "days": [_as_dict(item) for item in signals[:3] if isinstance(item, dict)], "source": "present_evidence.external_activation.official_day_signals" if signals else None, } def _topic_monthly_adjudication_summary(contracts: dict[str, Any], modules: dict[str, Any], route: str) -> dict[str, Any]: contract = _as_dict(contracts.get(route)) bundle = _as_dict(contract.get("strict_adjudication_bundle")) summary = _as_dict(bundle.get("monthly_adjudication_summary")) or _as_dict(contract.get("monthly_adjudication_summary")) if summary: return summary mapping = { "career": "career_strict_evidence", "relationship": "relationship_strict_evidence", "finance": "finance_strict_evidence", } strict = _as_dict(modules.get(mapping.get(route, ""))) return _as_dict(strict.get("monthly_adjudication_summary")) def build_guided_topics(report: dict[str, Any]) -> list[dict[str, Any]]: modules = _as_dict(report.get("modules")) contracts = _strict_contracts(report, modules) chart = _as_dict(report.get("chart") or modules.get("chart")) planets = _as_dict(chart.get("planets")) md, ad, md_start, md_end = _current_dasha(modules) md_label = f"{md or '-'} / {ad or '-'}" fbm = _as_dict(_as_dict(report.get("ai_prompt_pack")).get("evidence_snapshot")).get("functional_benefic_malefic") fbm = _as_dict(fbm) or _as_dict(modules.get("functional_benefic_malefic")) career_conv = _convergence_for(modules, "career", "status", "profession", "work") marriage_conv = _convergence_for(modules, "marriage", "partnership", "relationship") wealth_conv = _convergence_for(modules, "wealth", "finance", "income", "gain") relationship = _as_dict(modules.get("relationship_strict_evidence")) rel_judgement = _as_dict(relationship.get("event_judgement")) rel_present = _as_dict(relationship.get("present_evidence")) d9 = _as_dict(rel_present.get("d9_navamsa")) ul = _as_dict(rel_present.get("upapada_lagna")) dk = _as_dict(rel_present.get("darakaraka")) ketu_house = _as_dict(planets.get("Ketu")).get("house") topics = [ _topic( topic_id="relationship_partnership", title="婚恋与长期合作为什么是当前强主题", reality_value="帮助用户判断关系、合作、相亲、公开关系或长期承诺是否值得深入推进。", why="婚恋/合作不是靠用户主动问才触发；当前证据里第7宫、D9、UL、DK 与多系统时间层已经可读。", evidence=[ _evidence_line("Vimshottari", md_label), _evidence_line("Dasa 收敛", marriage_conv.get("convergence_level") or "not_found"), _evidence_line("D9", f"Asc={_as_dict(d9.get('Ascendant')).get('sign', '-')}; 7th={_as_dict(d9.get('_d9_analysis')).get('navamsa_7th_sign', '-')}"), _evidence_line("UL", f"{ul.get('sign', '-')} H{ul.get('house', '-')}"), _evidence_line("DK", f"{dk.get('dk_planet', '-')} H{dk.get('dk_house', '-')}"), _evidence_line("Strict verdict", rel_judgement.get("verdict") or "not_available"), ], confidence="medium" if marriage_conv or relationship else "low", vedastro=_vedastro_snapshot(modules, "marriage"), strict_audit_gate=_topic_audit_gate(contracts, "relationship"), monthly_adjudication_summary=_topic_monthly_adjudication_summary(contracts, modules, "relationship"), official_day_signal_summary=_topic_official_day_signal_summary(contracts, modules, "relationship"), questions=[ "我现在适合认真发展关系，还是更适合筛选和观察？", "我的伴侣画像、认识场景和相处风险是什么？", "未来哪些时间窗口适合推进关系公开或承诺？", ], priority=90 if marriage_conv else 65, ), _topic( topic_id="career_direction", title="事业定位是否正在重构", reality_value="帮助用户判断是继续深耕、换方向、做产品化，还是先修系统和长期资产。", why="事业主题需要把10宫、A10/D10、多系统 Dasha 与 VedAstro 事业雷达放在一起看。", evidence=[ _evidence_line("Vimshottari", md_label), _evidence_line("10宫触发", f"Ketu house={ketu_house}" if ketu_house else "check D10/A10"), _evidence_line("Dasa 收敛", career_conv.get("convergence_level") or "not_found"), _evidence_line("Functional layer", f"benefics={fbm.get('functional_benefics', [])}; malefics={fbm.get('functional_malefics', [])}"), ], confidence="medium" if career_conv or ketu_house == 10 else "low", vedastro=_vedastro_snapshot(modules, "career"), strict_audit_gate=_topic_audit_gate(contracts, "career"), monthly_adjudication_summary=_topic_monthly_adjudication_summary(contracts, modules, "career"), official_day_signal_summary=_topic_official_day_signal_summary(contracts, modules, "career"), questions=[ "我现在适合换方向还是继续深耕？", "2026 年事业吉利在哪里，不利在哪里？", "哪些月份适合推进项目、发布产品或谈合作？", ], priority=82 if career_conv or ketu_house == 10 else 60, ), _topic( topic_id="birth_time_rectification", title="出生时间是否需要微调", reality_value="帮助用户把婚恋、事业、财富应期从泛泛判断推进到可回验时间窗口。", why="D9、D10、UL、A10 对出生时间敏感；如果用户想问具体月份/日期，先校正时间更有价值。", evidence=[ _evidence_line("birth time", _as_dict(report.get("birth_info")).get("time", "-")), _evidence_line("sensitive layers", "D9 / D10 / UL / A10"), _evidence_line("current timing", f"{md_label}; {md_start or '-'} to {md_end or '-'}"), ], confidence="medium", vedastro=_vedastro_snapshot(modules, "marriage"), strict_audit_gate=_topic_audit_gate(contracts, "relationship"), monthly_adjudication_summary=_topic_monthly_adjudication_summary(contracts, modules, "relationship"), official_day_signal_summary=_topic_official_day_signal_summary(contracts, modules, "relationship"), questions=[ "我可以用过去事件校正出生时间吗？", "哪些人生事件最适合用来校正出生时间？", "我只知道一个时间区间，系统应该先问我哪些 yes/no 问题？", ], answer_mode="yes_no_or_free_text", priority=80, ), _topic( topic_id="wealth_risk", title="财富、借贷和交易风险怎样用数据拆开", reality_value="帮助用户把收入、现金流、借贷、买卖和投资风险分开判断，而不是只说财运好坏。", why="财富主题必须同时看2宫、11宫、D2/D11、Dasha 与 VedAstro wealth 标签。", evidence=[ _evidence_line("Vimshottari", md_label), _evidence_line("Dasa 收敛", wealth_conv.get("convergence_level") or "not_found"), _evidence_line("required vargas", "D2 / D11"), ], confidence="medium" if wealth_conv else "low", vedastro=_vedastro_snapshot(modules, "wealth"), strict_audit_gate=_topic_audit_gate(contracts, "finance"), monthly_adjudication_summary=_topic_monthly_adjudication_summary(contracts, modules, "finance"), official_day_signal_summary=_topic_official_day_signal_summary(contracts, modules, "finance"), questions=[ "2026 年哪些钱可以赚，哪些钱要避险？", "我适合靠项目、投资、合作还是长期积累赚钱？", "哪些时间窗口不适合借贷、买卖或大额投入？", ], priority=70 if wealth_conv else 50, ), ] topics.sort(key=lambda item: (-int(item.get("priority", 0)), item["id"])) return topics[:4]