Jyotisha/frontend/tests/rectification-dead-d9-choice-20260916.test.ts

import assert from "node:assert/strict";
import test from "node:test";
import { readFileSync } from "node:fs";

import { buildInferenceState } from "../src/lib/rectification-agentic/core/build-state.ts";
import {
  applyChoiceWithoutEvidence,
  previousInferenceFromReceipt,
  stampChoiceSchemaWithProbe,
} from "../src/lib/rectification-agentic/v9/inference-adapter.ts";

import {
  buildMethodFollowupPlan,
  yearlessPersonalityCanAsk,
  type MethodFollowup,
} from "../src/lib/rectification-agentic/v9/method-followup.ts";
import { choiceCardFromCaseDossier } from "../src/lib/rectification-agentic/v9/interview-state.ts";
import { rectificationFollowupCatalog } from "../src/lib/rectification-agentic/v9/decision-from-dossier.ts";
import {
  inferenceForPersistedAnswer,
  persistedDistinguishFocusStale,
} from "../src/lib/rectification-agentic/v9/answer-choice.ts";
import { expectedAnswerSchemaFor } from "../src/lib/rectification-agentic/v9/server-focus.ts";
import { buildChoiceFrame } from "../src/lib/rectification-agentic/v9/choice-card.ts";
import { buildRangeDelivery } from "../src/lib/rectification-agentic/v9/divergence-panel.ts";
import { parseWindowScan } from "../src/lib/rectification-agentic/v9/varga-observations.ts";
import {
  buildVargaDistinguishFields,
  withOwnedDistinguishProbes,
} from "../src/lib/rectification-agentic/v9/varga-distinguish-probe.ts";
import { rectificationQuestionGapState } from "../src/lib/rectification-surface-state.ts";
import { FOCUS_ID } from "./rectification-v9-test-support.ts";
import { rectificationChatSurface } from "./rectification-chat-surface.ts";

const OWNED_KEY = "d9_relationship:relationship_style";
const QUESTION_ID = "d9_relationship:relationship_style:score";

const DATED = [
  {
    status: "confirmed",
    domain: "health_pressure",
    datePrecision: "month",
    occurredFrom: "2019-03-01",
    occurredTo: "2019-03-31",
  },
  {
    status: "confirmed",
    domain: "career",
    datePrecision: "year",
    occurredFrom: "2018-01-01",
    occurredTo: "2018-12-31",
  },
  {
    status: "confirmed",
    domain: "education",
    datePrecision: "year",
    occurredFrom: "2016-01-01",
    occurredTo: "2016-12-31",
  },
  {
    status: "confirmed",
    domain: "occupation",
    datePrecision: "unknown",
    occurredFrom: null,
    occurredTo: null,
  },
];

const D24 = {
  id: "contrast:varga.d24.白羊座|金牛座|双子座|巨蟹座|狮子座|处女座",
  semantic_key: "varga.d24.白羊座|金牛座|双子座|巨蟹座|狮子座|处女座",
  candidate_split_hash: "set:varga.d24.白羊座|金牛座|双子座|巨蟹座|狮子座|处女座",
  domain: "education",
  year: 0,
  question: "学业对照",
  candidate_ids: ["04:48", "04:59"],
  expected_outcomes: [
    { answer_class: "yes" as const, supports: ["04:48"], conflicts: ["04:59"] },
    { answer_class: "weak_yes" as const, supports: ["04:59"], conflicts: ["04:48"] },
    { answer_class: "no" as const, supports: [], conflicts: [] },
    { answer_class: "unsure" as const, supports: [], conflicts: [] },
  ],
  information_gain: 0.9,
  source: "engine",
  choice_kind: "event_quality" as const,
};

/** Engine window scan as it arrives on the decision receipt. */
const WINDOW_SCAN_RECEIPT = {
  scanned: true,
  d9_lagna_count: 2,
  d10_lagna_count: 1,
  d9_candidates_differ: true,
  d10_candidates_differ: false,
  d9_sign_names: ["天蝎座", "天秤座"],
  d10_sign_names: ["巨蟹座"],
  transitions: [
    { layer: "d9", at: "04:53", from_sign: "天蝎座", to_sign: "天秤座" },
    { layer: "d10", at: "04:40", from_sign: "巨蟹座", to_sign: "巨蟹座" },
  ],
};

const WINDOW = parseWindowScan(WINDOW_SCAN_RECEIPT)!;

const CANDIDATES = [
  { id: "04:48", time: "04:48" },
  { id: "04:53", time: "04:53" },
  { id: "04:59", time: "04:59" },
];

/** The persisted state: engine probes only, exactly as the receipt stores it. */
function persistedState() {
  return buildInferenceState({
    range_start: "04:48",
    range_end: "05:07",
    candidates: [
      { id: "04:48", time: "04:48", relative_support: 44 },
      { id: "04:53", time: "04:53", relative_support: 35 },
      { id: "04:59", time: "04:59", relative_support: 21 },
    ],
    events: Array.from({ length: 5 }, (_, index) => ({
      id: `e${index}`,
      domain: "health",
      year: 2019,
      precision: "month" as const,
    })),
    probes: [D24],
  });
}

function receipt() {
  return { inference_state: persistedState(), window_scan: WINDOW_SCAN_RECEIPT };
}

/**
 * A D9 style focus as it was persisted before the 2026-09-17 (b) decision:
 * its identity is the layer's own key, and its probe lives nowhere but the
 * receipt's window scan.
 */
function legacyD9Followup(): MethodFollowup {
  const fields = buildVargaDistinguishFields({
    methodId: "d9_relationship",
    askTheme: "relationship_style",
    transitions: WINDOW.transitions,
    candidates: CANDIDATES,
  });
  assert.ok(fields);
  const followup = {
    method_id: "d9_relationship",
    intent: "distinguish_candidates",
    ask_theme: "relationship_style",
    domain: "relationship",
    kind_hint: "relationship_change",
    user_prompt_hint: "当前候选在关系主题上仍分不开。",
    source: "varga_observation",
    must_not_label: false,
    choice_frame: null,
    ...fields,
  } as MethodFollowup;
  const frame = buildChoiceFrame(followup, {
    evidence: DATED,
    probes: [{
      year: 0,
      year_label: "当前这几个候选",
      domain: "relationship",
      event_family: "开始认真关系、分手或结婚",
      source: "dasha_activation",
      tracks: ["vimshottari", "narayana"],
      tracks_agree: true,
      unique_minute_claim: false,
      user_meaning: followup.user_prompt_hint,
      role: "distinguish",
      phase: "candidate_discriminator",
      information_gain: followup.information_gain,
      semantic_key: followup.semantic_key,
      candidate_split_hash: followup.candidate_split_hash,
      candidate_ids: followup.candidate_ids,
      expected_outcomes: followup.expected_outcomes,
      choice_kind: "varga_style" as const,
      style_options: followup.style_options,
    }],
  });
  assert.ok(frame);
  return { ...followup, choice_frame: frame };
}

function persistedSchema(): Record<string, unknown> {
  const followup = legacyD9Followup();
  const schema = expectedAnswerSchemaFor(
    followup.choice_frame!,
    QUESTION_ID,
    receipt(),
    followup,
  );
  assert.ok(schema);
  return schema;
}

test("stamping rebuilds the owned probe from the receipt instead of borrowing D24 (BUG-912/915)", () => {
  const state = persistedState();
  const borrowed = stampChoiceSchemaWithProbe({
    choice: {
      options: [
        { key: "A", answer_class: "yes" },
        { key: "B", answer_class: "weak_yes" },
        { key: "C", answer_class: "no" },
        { key: "D", answer_class: "unsure" },
      ],
    },
  }, state, QUESTION_ID);
  assert.notEqual(borrowed.probe_id, D24.id);

  // The persisted receipt itself never carries the owned probe.
  const stored = previousInferenceFromReceipt(receipt());
  assert.ok(stored);
  assert.equal(stored.probes.some((probe) => probe.semantic_key === OWNED_KEY), false);
  const rebuilt = withOwnedDistinguishProbes(stored, receipt());
  assert.ok(rebuilt?.probes.some((probe) => probe.semantic_key === OWNED_KEY));

  const schema = persistedSchema();
  assert.equal(schema.semantic_key, OWNED_KEY);
  assert.equal(schema.probe_id, `probe:${OWNED_KEY}`);
  assert.notEqual(String(schema.probe_id ?? ""), D24.id);
});

test("the production answer path applies a persisted owned-probe choice (BUG-915)", () => {
  const schema = persistedSchema();
  const answerInput = {
    choiceKey: "C",
    schema,
    questionId: QUESTION_ID,
    domain: "relationship",
    classifiedFrom: "choice" as const,
  };
  // Without the rebuild the same schema is unanswerable: that was the P0.
  const withoutRebuild = applyChoiceWithoutEvidence(previousInferenceFromReceipt(receipt())!, answerInput);
  assert.equal(withoutRebuild.applied, false);
  assert.equal(withoutRebuild.reason, "stale_probe");

  const applied = applyChoiceWithoutEvidence(inferenceForPersistedAnswer(receipt())!, answerInput);
  assert.equal(applied.reason, "applied");
  assert.equal(applied.applied, true);
  assert.equal(applied.state.answered_probes.at(-1)?.semantic_key, OWNED_KEY);
  assert.ok(!applied.state.answered_probes.some((row) => row.probe_id === D24.id));
});

test("GET projects the persisted D9 card from the receipt alone (BUG-915)", () => {
  const schema = persistedSchema();
  const card = choiceCardFromCaseDossier({
    evidence: DATED,
    conversationSummary: {
      activeFocus: {
        id: FOCUS_ID,
        questionId: QUESTION_ID,
        intent: "distinguish_candidates",
        targetDomain: "relationship",
        targetKind: null,
        expectedAnswerSchema: schema,
      },
      declinedSkippedTopics: [],
    },
    latestResult: {
      resultId: "result-1",
      decisionReceipt: receipt(),
      selectionAllowed: false,
      confirmationAllowed: false,
      candidates: [
        { time: "04:48", rank: 1, relativeSupport: 44 },
        { time: "04:53", rank: 2, relativeSupport: 35 },
        { time: "04:59", rank: 3, relativeSupport: 21 },
      ],
    },
    case: { acceptedTime: null, status: "active", stage: "minute" },
  });
  assert.ok(card, "GET must render the persisted focus");
  assert.equal(card.question_id, QUESTION_ID);
  assert.equal(card.options.length, 4);
});

test("idle persist does not supersede a focus whose probe is rebuilt (BUG-915)", () => {
  const schema = persistedSchema();
  const focus = { intent: "distinguish_candidates", expectedAnswerSchema: schema };
  // The raw receipt state has no owned probe: that is what superseded the
  // fresh focus on every idle persist.
  assert.equal(persistedDistinguishFocusStale(previousInferenceFromReceipt(receipt()), focus), true);
  assert.equal(persistedDistinguishFocusStale(inferenceForPersistedAnswer(receipt()), focus), false);

  // A changed candidate set still expires the focus (BUG-559 stays).
  const movedReceipt = {
    window_scan: WINDOW_SCAN_RECEIPT,
    inference_state: buildInferenceState({
      range_start: "04:48",
      range_end: "05:07",
      candidates: [
        { id: "04:48", time: "04:48", relative_support: 60 },
        { id: "04:59", time: "04:59", relative_support: 40 },
      ],
      events: persistedState().events,
      probes: [D24],
    }),
  };
  assert.equal(persistedDistinguishFocusStale(inferenceForPersistedAnswer(movedReceipt), focus), true);
});

test("every state read that can touch an owned probe rebuilds it (BUG-915 source contract)", () => {
  const sites = [
    "src/lib/rectification-agentic/v9/server-focus.ts",
    "src/lib/rectification-agentic/v9/interview-state.ts",
  ];
  for (const site of sites) {
    const source = readFileSync(new URL(`../${site}`, import.meta.url), "utf8");
    assert.match(source, /withOwnedDistinguishProbes\(/, site);
  }
  const answerChoice = readFileSync(
    new URL("../src/lib/rectification-agentic/v9/answer-choice.ts", import.meta.url),
    "utf8",
  );
  // The tap answer and the idle supersede check both read the rebuilt state.
  assert.match(answerChoice, /const previous = inferenceForPersistedAnswer\(receipt\);/);
  assert.match(answerChoice, /const inferenceForStale = withOwnedDistinguishProbes\(/);
  const tools = readFileSync(new URL("../src/mastra/rectification-v9-tools.ts", import.meta.url), "utf8");
  // The typed answer goes through the same helper as the tap.
  assert.match(tools, /const previous = inferenceForPersistedAnswer\(/);
});

const REL_2020_PROBE = {
  year: 2020,
  year_label: "2020 年前后",
  domain: "relationship" as const,
  event_family: "开始认真关系、分手或结婚",
  source: "dasha_activation" as const,
  tracks: ["vimshottari", "narayana"] as const,
  tracks_agree: true,
  unique_minute_claim: false as const,
  user_meaning: "2020 年感情线",
  role: "distinguish" as const,
  phase: "candidate_discriminator" as const,
  information_gain: 0.5,
  semantic_key: "relationship.2020",
  candidate_split_hash: "set:relationship.2020",
  candidate_ids: ["04:48", "04:53", "04:59"],
  expected_outcomes: [
    { answer_class: "yes" as const, supports: ["04:48"], conflicts: ["04:53", "04:59"] },
    { answer_class: "weak_yes" as const, supports: ["04:53"], conflicts: ["04:48", "04:59"] },
    { answer_class: "no" as const, supports: ["04:59"], conflicts: ["04:48", "04:53"] },
    { answer_class: "unsure" as const, supports: [], conflicts: [] },
  ],
  choice_kind: "existence" as const,
};

/** Every dated collect line already closed, as in the 2026-09-17 real run. */
const CLOSED_COLLECT = [
  "family",
  "education",
  "finance",
  "relocation",
  "health_pressure",
  "career",
  "relationship",
].map((domain) => ({
  question_id: `collect:targeted:${domain}`,
  target_kind: `targeted:${domain}`,
  domain,
  status: "declined",
  intent: "collect_method_evidence",
}));

function planWithD9Split(input: { askedProbeKeys: readonly string[] }) {
  return buildMethodFollowupPlan({
    evidence: DATED,
    observations: [
      { layer: "d9", candidates_differ: true, ask_theme: "relationship_style" },
      { layer: "d10", candidates_differ: false, ask_theme: null },
    ],
    windowScan: WINDOW,
    inferenceState: persistedState(),
    sessionOutcome: "discriminate_candidates",
    precisionStage: "d9_refine",
    eventProbes: [REL_2020_PROBE],
    askedProbeKeys: input.askedProbeKeys,
    closedCollectFocuses: CLOSED_COLLECT,
    topCandidateTimes: ["04:48", "04:53", "04:59"],
    candidateRanges: CANDIDATES.map((row) => ({ id: row.id, time: row.time })),
  });
}

test("a varga style question is never a scoring discriminator (2026-09-17 decision b)", () => {
  // The engine's relationship probe is already asked, so nothing dates this
  // line: before the decision this is where 「你更接近哪一种相处方式」 came from.
  const plan = planWithD9Split({ askedProbeKeys: ["relationship.2020"] });
  const next = plan.next_followup;
  assert.notEqual(next?.semantic_key, OWNED_KEY);
  assert.notEqual(next?.choice_kind, "varga_style");
  assert.doesNotMatch(next?.choice_frame?.prompt ?? "", /更接近哪一种/);
  assert.equal(
    next?.intent === "distinguish_candidates"
      && (next.source === "varga_observation" || next.source === "precision_stage"),
    false,
    JSON.stringify({ intent: next?.intent, source: next?.source, key: next?.semantic_key }),
  );
  assert.ok(
    plan.dropped_probes.some((row) => (
      row.semantic_key === "d9_relationship" && row.reason === "frameless_distinguish"
    )),
    JSON.stringify(plan.dropped_probes),
  );
});

test("the D9 line is still asked when the engine dates it (2026-09-17 decision b)", () => {
  const plan = planWithD9Split({ askedProbeKeys: [] });
  const next = plan.next_followup;
  assert.equal(next?.method_id, "d9_relationship");
  assert.equal(next?.intent, "distinguish_candidates");
  assert.equal(next?.semantic_key, REL_2020_PROBE.semantic_key);
  assert.equal(next?.choice_kind, "existence");
  assert.match(next?.choice_frame?.prompt ?? "", /2020/);
});

test("a rebuilt owned probe never becomes an askable discriminator (decision b)", () => {
  // Answering an old style focus writes the rebuilt probes into the receipt.
  const answered = withOwnedDistinguishProbes(previousInferenceFromReceipt(receipt()), receipt())!;
  const owned = answered.probes.find((probe) => probe.semantic_key === OWNED_KEY);
  assert.ok(owned);
  const catalog = rectificationFollowupCatalog(
    { resultId: "result-1", decisionReceipt: { ...receipt(), inference_state: answered } },
    DATED,
  );
  assert.equal(catalog.eventProbes.some((probe) => probe.semantic_key === OWNED_KEY), false);
  assert.equal(
    (catalog.contrastPacket?.probes ?? []).some((probe) => probe.semanticKey === OWNED_KEY),
    false,
  );
});

test("a dead tap card never shares the screen with the collect-wait placeholder (BUG-917)", () => {
  const base = {
    liveQuestionVisible: false,
    questionMissing: true,
    questionLoadFailed: false,
    busy: false,
    readonly: false,
    regenerating: false,
    snapshotLoaded: true,
    resumableCase: true,
    retryAttempts: 0,
    collectWaiting: true,
  };
  assert.equal(rectificationQuestionGapState(base), "collect_waiting");
  assert.equal(
    rectificationQuestionGapState({ ...base, unansweredDeadChoice: true }),
    "unavailable",
  );
  // 原值: 读 rectification-agentic-chat.tsx 单文件。新值: rectificationChatSurface（容器 + 拆出的 hook / 参数函数 / 块，见 rectification-chat-surface.ts）。原因: TASK-rectification-code-split-20260926 只搬不改，整文件断言跟着代码走；切片断言另行改为调用函数。
  const chat = rectificationChatSurface;
  assert.match(chat, /unansweredDeadChoice: unansweredDeadChoiceOnMessages,/);
  assert.match(chat, /latestSettledAssistant\.question\.status === "superseded"/);
  const entry = readFileSync(
    new URL("../src/components/rectification-message-entry.tsx", import.meta.url),
    "utf8",
  );
  assert.match(entry, /question\.status === "superseded" && !question\.answer_option/);
});

test("five dated events do not hold for yearless personality (BUG-913 closed_by_design)", () => {
  assert.equal(yearlessPersonalityCanAsk({ datedCount: 5, candidatesSeparated: false }), false);
  assert.equal(yearlessPersonalityCanAsk({ datedCount: 0, candidatesSeparated: false, topCandidateTimes: ["04:48", "04:59"] }), true);
});

test("nakshatra opposite poles are not both lifted as shared traits (BUG-914)", () => {
  const earlier = "希望两边都能说得过去";
  const later = "必要时会直接选边";
  const delivery = buildRangeDelivery({
    inference: persistedState(),
    publicCandidates: [
      { candidateId: "a", time: "04:48" },
      { candidateId: "b", time: "04:53" },
      { candidateId: "c", time: "04:59" },
    ],
    credibleRange: ["04:48", "04:59"],
    representativeTime: "04:59",
    nakshatraBoundary: {
      near_boundary: true,
      user_meaning: `A：${earlier}。B：${later}。`,
      options: [
        { key: "A", time_bias: "earlier", traits: [earlier] },
        { key: "B", time_bias: "later", traits: [later] },
      ],
    },
  });
  const shared = delivery.shared_traits.join(" ");
  assert.equal(shared.includes(earlier) && shared.includes(later), false);
});