278 lines
9.3 KiB
TypeScript
278 lines
9.3 KiB
TypeScript
import assert from "node:assert/strict";
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import test from "node:test";
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import { buildInferenceState } from "../src/lib/rectification-agentic/core/build-state.ts";
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import {
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applyChoiceWithoutEvidence,
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stampChoiceSchemaWithProbe,
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} from "../src/lib/rectification-agentic/v9/inference-adapter.ts";
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import {
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projectRectificationChoiceCard,
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yearlessPersonalityCanAsk,
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type MethodFollowup,
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} from "../src/lib/rectification-agentic/v9/method-followup.ts";
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import { expectedAnswerSchemaFor } from "../src/lib/rectification-agentic/v9/server-focus.ts";
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import { buildChoiceFrame } from "../src/lib/rectification-agentic/v9/choice-card.ts";
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import { buildRangeDelivery } from "../src/lib/rectification-agentic/v9/divergence-panel.ts";
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import { parseWindowScan } from "../src/lib/rectification-agentic/v9/varga-observations.ts";
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import {
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attachVargaDistinguishIdentity,
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withFollowupOwnedProbe,
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} from "../src/lib/rectification-agentic/v9/varga-distinguish-probe.ts";
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import { FOCUS_ID } from "./rectification-v9-test-support.ts";
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const DATED = [
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{
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status: "confirmed",
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domain: "health_pressure",
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datePrecision: "month",
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occurredFrom: "2019-03-01",
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occurredTo: "2019-03-31",
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},
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{
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status: "confirmed",
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domain: "career",
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datePrecision: "year",
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occurredFrom: "2018-01-01",
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occurredTo: "2018-12-31",
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},
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{
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status: "confirmed",
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domain: "education",
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datePrecision: "year",
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occurredFrom: "2016-01-01",
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occurredTo: "2016-12-31",
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},
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{
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status: "confirmed",
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domain: "occupation",
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datePrecision: "unknown",
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occurredFrom: null,
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occurredTo: null,
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},
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];
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const D24 = {
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id: "contrast:varga.d24.白羊座|金牛座|双子座|巨蟹座|狮子座|处女座",
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semantic_key: "varga.d24.白羊座|金牛座|双子座|巨蟹座|狮子座|处女座",
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candidate_split_hash: "set:varga.d24.白羊座|金牛座|双子座|巨蟹座|狮子座|处女座",
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domain: "education",
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year: 0,
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question: "学业对照",
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candidate_ids: ["04:48", "04:59"],
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expected_outcomes: [
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{ answer_class: "yes" as const, supports: ["04:48"], conflicts: ["04:59"] },
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{ answer_class: "weak_yes" as const, supports: ["04:59"], conflicts: ["04:48"] },
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{ answer_class: "no" as const, supports: [], conflicts: [] },
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{ answer_class: "unsure" as const, supports: [], conflicts: [] },
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],
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information_gain: 0.9,
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source: "engine",
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choice_kind: "event_quality" as const,
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};
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const WINDOW = parseWindowScan({
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scanned: true,
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d9_lagna_count: 2,
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d10_lagna_count: 1,
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d9_candidates_differ: true,
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d10_candidates_differ: false,
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d9_sign_names: ["天蝎座", "天秤座"],
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d10_sign_names: ["巨蟹座"],
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transitions: [
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{ layer: "d9", at: "04:53", from_sign: "天蝎座", to_sign: "天秤座" },
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{ layer: "d10", at: "04:40", from_sign: "巨蟹座", to_sign: "巨蟹座" },
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],
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});
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function state() {
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return buildInferenceState({
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range_start: "04:48",
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range_end: "05:07",
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candidates: [
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{ id: "04:48", time: "04:48", relative_support: 44 },
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{ id: "04:53", time: "04:53", relative_support: 35 },
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{ id: "04:59", time: "04:59", relative_support: 21 },
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],
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events: Array.from({ length: 5 }, (_, index) => ({
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id: `e${index}`,
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domain: "health",
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year: 2019,
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precision: "month" as const,
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})),
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probes: [D24],
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});
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}
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function d9Followup() {
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const attached = attachVargaDistinguishIdentity({
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method_id: "d9_relationship",
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intent: "distinguish_candidates",
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ask_theme: "relationship_style",
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domain: "relationship",
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kind_hint: "relationship_change",
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user_prompt_hint: "当前候选在关系主题上仍分不开。",
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source: "varga_observation",
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must_not_label: false,
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choice_frame: null,
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}, {
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windowScan: WINDOW,
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candidates: [
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{ id: "04:48", time: "04:48" },
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{ id: "04:53", time: "04:53" },
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{ id: "04:59", time: "04:59" },
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],
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}) as MethodFollowup;
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const frame = buildChoiceFrame(attached, {
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evidence: DATED,
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probes: attached.style_options ? [{
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year: 0,
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year_label: "当前这几个候选",
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domain: "relationship",
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event_family: "开始认真关系、分手或结婚",
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source: "dasha_activation",
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tracks: ["vimshottari", "narayana"],
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tracks_agree: true,
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unique_minute_claim: false,
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user_meaning: attached.user_prompt_hint,
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role: "distinguish",
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phase: "candidate_discriminator",
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information_gain: attached.information_gain,
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semantic_key: attached.semantic_key,
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candidate_split_hash: attached.candidate_split_hash,
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candidate_ids: attached.candidate_ids,
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expected_outcomes: attached.expected_outcomes,
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choice_kind: "varga_style" as const,
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style_options: attached.style_options,
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}] : [] as never,
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});
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return { ...attached, choice_frame: frame } as MethodFollowup;
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}
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test("year-stage D9 followup does not borrow the D24 contrast probe (BUG-912)", () => {
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const inference = state();
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const borrowed = stampChoiceSchemaWithProbe({
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choice: {
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options: [
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{ key: "A", answer_class: "yes" },
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{ key: "B", answer_class: "weak_yes" },
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{ key: "C", answer_class: "no" },
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{ key: "D", answer_class: "unsure" },
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],
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},
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}, inference, "d9_relationship:relationship_style:score");
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assert.notEqual(borrowed.probe_id, D24.id);
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const followup = d9Followup();
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assert.equal(followup.semantic_key, "d9_relationship:relationship_style");
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assert.ok(followup.choice_frame);
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const schema = expectedAnswerSchemaFor(
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followup.choice_frame!,
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followup.choice_frame!.question_id,
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{ inference_state: inference, window_scan: WINDOW },
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followup,
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);
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assert.ok(schema);
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assert.equal(schema.semantic_key, "d9_relationship:relationship_style");
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assert.notEqual(String(schema.probe_id ?? ""), D24.id);
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assert.match(String(schema.probe_id ?? ""), /d9_relationship:relationship_style/);
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const applied = applyChoiceWithoutEvidence(withFollowupOwnedProbe(inference, followup)!, {
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choiceKey: "C",
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schema,
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questionId: "d9_relationship:relationship_style:score",
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domain: "relationship",
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classifiedFrom: "choice",
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});
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assert.equal(applied.applied, true);
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assert.equal(applied.state.answered_probes.at(-1)?.semantic_key, "d9_relationship:relationship_style");
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assert.ok(!applied.state.answered_probes.some((row) => row.probe_id === D24.id));
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});
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test("GET projects the persisted distinguish copy when its probe is still live (BUG-912)", () => {
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const inference = state();
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const followup = d9Followup();
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const schema = expectedAnswerSchemaFor(
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followup.choice_frame!,
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"d9_relationship:relationship_style:score",
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{ inference_state: inference, window_scan: WINDOW },
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followup,
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);
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const withOwned = buildInferenceState({
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range_start: "04:48",
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range_end: "05:07",
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candidates: [
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{ id: "04:48", time: "04:48", relative_support: 44 },
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{ id: "04:53", time: "04:53", relative_support: 35 },
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{ id: "04:59", time: "04:59", relative_support: 21 },
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],
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events: inference.events,
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probes: [
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D24,
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{
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id: String(schema?.probe_id),
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semantic_key: String(schema?.semantic_key),
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candidate_split_hash: String(schema?.candidate_split_hash),
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domain: "relationship",
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year: 0,
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question: "D9",
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candidate_ids: ["04:48", "04:59"],
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expected_outcomes: D24.expected_outcomes,
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information_gain: 0.4,
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source: "varga_observation",
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choice_kind: "varga_style" as const,
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style_options: followup.style_options as never,
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},
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],
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});
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const card = projectRectificationChoiceCard({
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evidence: DATED,
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activeFocus: {
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id: FOCUS_ID,
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questionId: "d9_relationship:relationship_style:score",
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intent: "distinguish_candidates",
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targetDomain: "relationship",
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targetKind: null,
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expectedAnswerSchema: schema,
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},
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observations: [{ layer: "d9", candidates_differ: true, ask_theme: "relationship_style" }],
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windowScan: WINDOW,
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inferenceState: withOwned,
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sessionOutcome: "collect_evidence",
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caseRevision: 1,
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});
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assert.equal(card?.question_id, "d9_relationship:relationship_style:score");
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assert.equal(card?.options.length, 4);
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});
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test("five dated events do not hold for yearless personality (BUG-913 closed_by_design)", () => {
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assert.equal(yearlessPersonalityCanAsk({ datedCount: 5, candidatesSeparated: false }), false);
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assert.equal(yearlessPersonalityCanAsk({ datedCount: 0, candidatesSeparated: false, topCandidateTimes: ["04:48", "04:59"] }), true);
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});
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test("nakshatra opposite poles are not both lifted as shared traits (BUG-914)", () => {
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const earlier = "希望两边都能说得过去";
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const later = "必要时会直接选边";
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const delivery = buildRangeDelivery({
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inference: state(),
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publicCandidates: [
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{ candidateId: "a", time: "04:48" },
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{ candidateId: "b", time: "04:53" },
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{ candidateId: "c", time: "04:59" },
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],
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credibleRange: ["04:48", "04:59"],
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representativeTime: "04:59",
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nakshatraBoundary: {
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near_boundary: true,
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user_meaning: `A：${earlier}。B：${later}。`,
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options: [
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{ key: "A", time_bias: "earlier", traits: [earlier] },
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{ key: "B", time_bias: "later", traits: [later] },
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],
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},
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});
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const shared = delivery.shared_traits.join(" ");
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assert.equal(shared.includes(earlier) && shared.includes(later), false);
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});
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