Initial React project
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Johan
322
src/mvvm/viewmodels/SimulatorEvaluationViewModel.ts
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322
src/mvvm/viewmodels/SimulatorEvaluationViewModel.ts
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import { SimulationService } from '../services/simulation.service';
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interface RecordLike {
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[key: string]: unknown;
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}
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export interface SimulatorEvaluationSelectionContext {
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companyName?: string;
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dateLabel?: string;
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title?: string;
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}
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export interface EvaluationImprovementItem {
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id: string;
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title: string;
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behavior: string;
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effect: string;
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nextStep: string;
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}
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export interface SimulatorEvaluationData {
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companyName: string;
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dateLabel: string;
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evaluationLabel: string;
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interviewerEvaluationBody: string;
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interviewerEvaluationLead: string;
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interviewerEvaluationTitle: string;
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interviewerScore: number;
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interviewTitle: string;
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recommendations: string[];
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selfScore: number;
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strengths: string[];
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suggestions: EvaluationImprovementItem[];
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}
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function asRecord(value: unknown): RecordLike | null {
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return typeof value === 'object' && value !== null ? (value as RecordLike) : null;
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}
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function asString(value: unknown): string {
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return typeof value === 'string' ? value : '';
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}
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function asNumber(value: unknown): number | null {
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if (typeof value === 'number' && Number.isFinite(value)) {
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return value;
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}
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if (typeof value === 'string') {
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const parsed = Number(value);
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return Number.isFinite(parsed) ? parsed : null;
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}
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return null;
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}
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function asStringArray(value: unknown): string[] {
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if (!Array.isArray(value)) {
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return [];
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}
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return value.map((item) => asString(item).trim()).filter(Boolean);
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}
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function pickString(root: RecordLike | null, keys: string[]): string {
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if (!root) {
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return '';
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}
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for (const key of keys) {
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const value = asString(root[key]).trim();
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if (value) {
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return value;
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}
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}
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return '';
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}
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function pickNumber(root: RecordLike | null, keys: string[]): number | null {
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if (!root) {
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return null;
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}
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for (const key of keys) {
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const value = asNumber(root[key]);
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if (value !== null) {
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return value;
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}
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}
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return null;
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}
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function formatDateLabel(value: string): string {
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if (!value) {
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return '';
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}
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const date = new Date(value);
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if (Number.isNaN(date.getTime())) {
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return value;
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}
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return new Intl.DateTimeFormat('da-DK', {
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day: '2-digit',
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month: 'long',
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year: 'numeric',
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}).format(date);
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}
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function normalizeScore(value: number | null, fallback: number): number {
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if (value === null) {
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return fallback;
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}
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return Math.max(0, Math.min(10, Math.round(value)));
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}
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const FALLBACK_SUGGESTIONS: EvaluationImprovementItem[] = [
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{
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id: '1',
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title: 'Mere struktur og korthed i dine svar',
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behavior: 'Du gav nogle svar, der blev lange og gentagende i stedet for fokuserede pa kernen.',
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effect: 'Det kan gore det svaerere for intervieweren hurtigt at vurdere din erfaring og beslutninger.',
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nextStep: 'Svar i 3 trin: pointe, konkret eksempel, resultat. Sigt efter 30-60 sekunder pr. svar.',
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},
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{
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id: '2',
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title: 'Flere konkrete eksempler pa performance i service',
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behavior: 'Du fortalte om ansvar, men gav fa konkrete scenarier med handling og resultat.',
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effect: 'Uden konkrete cases bliver niveau og paalidelighed svaerere at validere.',
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nextStep: 'Forbered 2-3 STAR-historier med tydelig situation, handling og maelbart resultat.',
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},
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{
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id: '3',
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title: 'Gor din motivation mere maelrettet virksomheden',
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behavior: 'Motivationen var positiv, men ikke altid koblet direkte til virksomhedens drift og behov.',
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effect: 'Du kan fremsta generelt motiveret i stedet for specifikt relevant for rollen.',
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nextStep: 'Naevn 2-3 konkrete grunde til, at netop deres setup matcher din erfaring.',
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},
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{
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id: '4',
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title: 'Konkretiser kvalitet og sikkerhed i praksis',
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behavior: 'Du naevnte standarder og certificeringer, men beskrev fa daglige rutiner.',
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effect: 'Det reducerer tydeligheden omkring, hvordan du arbejder sikkert i travle perioder.',
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nextStep: 'Beskriv faste rutiner for kontrol, logning og hurtig korrektion under pres.',
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},
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];
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const FALLBACK_STRENGTHS = [
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'Du viser relevant erfaring for rollen og kommunikerer ro under pres.',
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'Du arbejder struktureret med kvalitet og timing i service.',
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'Du har en moden team-tilgang med fokus pa samarbejde.',
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'Du kobler dine svar til konkrete arbejdsrutiner og drift.',
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'Du fremstar stabil og ansvarlig i hektiske situationer.',
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];
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const FALLBACK_RECOMMENDATIONS = [
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'Forbered 3 korte STAR-historier med maelbare resultater.',
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'Lav en 60-sekunders pitch af din profil og vaerdiskabelse.',
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'Research virksomheden i 10-15 minutter inden samtalen.',
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'Forbered 4-5 konkrete spoergsmaal om rolle og forventninger.',
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'Afslut svar med resultat, sa din effekt bliver tydelig.',
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];
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const FALLBACK_DATA: SimulatorEvaluationData = {
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companyName: 'Ukendt virksomhed',
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dateLabel: 'Nyligt',
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evaluationLabel: 'Interview Feedback',
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interviewerEvaluationTitle: 'Interviewer evaluering',
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interviewerEvaluationLead: 'Du er godt med. Din praestation viste styrker der matcher stillingen.',
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interviewerEvaluationBody:
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'Du viste relevante kompetencer og en stabil tilgang under pres. Du kan staerke dit indtryk yderligere ved at svare mere struktureret og bruge flere konkrete resultateksempler.',
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interviewTitle: 'Stilling',
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interviewerScore: 8,
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selfScore: 5,
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strengths: FALLBACK_STRENGTHS,
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recommendations: FALLBACK_RECOMMENDATIONS,
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suggestions: FALLBACK_SUGGESTIONS,
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};
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function mapSuggestion(item: unknown, index: number): EvaluationImprovementItem | null {
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const source = asRecord(item);
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if (!source) {
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return null;
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}
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const title = pickString(source, ['title', 'heading', 'name', 'subject']);
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const behavior = pickString(source, ['behavior', 'adfaerd', 'observation', 'issue']);
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const effect = pickString(source, ['effect', 'impact', 'consequence']);
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const nextStep = pickString(source, ['next_step', 'nextStep', 'recommendation', 'suggestion']);
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if (!title && !behavior && !effect && !nextStep) {
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return null;
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}
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return {
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id: asString(source.id) || String(index + 1),
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title: title || `Forbedringspunkt ${index + 1}`,
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behavior: behavior || 'Ingen detaljer tilgaengelige.',
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effect: effect || 'Ingen detaljer tilgaengelige.',
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nextStep: nextStep || 'Ingen detaljer tilgaengelige.',
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};
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}
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function extractSuggestions(root: RecordLike | null): EvaluationImprovementItem[] {
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const candidates = [
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root?.suggestions,
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root?.improvements,
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root?.improvement_points,
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root?.feedback_points,
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asRecord(root?.evaluation)?.suggestions,
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asRecord(root?.evaluation)?.improvements,
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];
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for (const candidate of candidates) {
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if (!Array.isArray(candidate)) {
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continue;
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}
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const mapped = candidate
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.map((item, index) => mapSuggestion(item, index))
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.filter((item): item is EvaluationImprovementItem => Boolean(item));
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if (mapped.length > 0) {
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return mapped;
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}
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}
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return FALLBACK_SUGGESTIONS;
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}
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function extractStringList(root: RecordLike | null, keys: string[], fallback: string[]): string[] {
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for (const key of keys) {
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const values = asStringArray(root?.[key]);
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if (values.length > 0) {
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return values;
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}
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}
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const evaluation = asRecord(root?.evaluation);
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for (const key of keys) {
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const values = asStringArray(evaluation?.[key]);
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if (values.length > 0) {
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return values;
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}
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}
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return fallback;
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}
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export class SimulatorEvaluationViewModel {
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constructor(private readonly simulationService: SimulationService = new SimulationService()) {}
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async getEvaluation(interviewId: string, context?: SimulatorEvaluationSelectionContext): Promise<SimulatorEvaluationData> {
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try {
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const payload = await this.simulationService.getInterviewEvaluation(interviewId);
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const root = asRecord(payload);
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const evaluation = asRecord(root?.evaluation);
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const companyName = pickString(root, ['company_name', 'companyName'])
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|| pickString(evaluation, ['company_name', 'companyName'])
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|| context?.companyName
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|| FALLBACK_DATA.companyName;
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const interviewTitle = pickString(root, ['job_title', 'job_name', 'title'])
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|| pickString(evaluation, ['job_title', 'job_name', 'title'])
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|| context?.title
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|| FALLBACK_DATA.interviewTitle;
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const rawDate = pickString(root, ['interview_date', 'created_at', 'date'])
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|| pickString(evaluation, ['interview_date', 'created_at', 'date']);
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const dateLabel = formatDateLabel(rawDate) || context?.dateLabel || FALLBACK_DATA.dateLabel;
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const interviewerEvaluationLead = pickString(root, ['interviewer_evaluation_lead', 'lead'])
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|| pickString(evaluation, ['interviewer_evaluation_lead', 'lead'])
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|| FALLBACK_DATA.interviewerEvaluationLead;
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const interviewerEvaluationBody = pickString(root, ['interviewer_evaluation', 'summary', 'feedback'])
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|| pickString(evaluation, ['interviewer_evaluation', 'summary', 'feedback'])
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|| FALLBACK_DATA.interviewerEvaluationBody;
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const interviewerEvaluationTitle = pickString(root, ['evaluation_title', 'interviewer_title'])
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|| pickString(evaluation, ['evaluation_title', 'interviewer_title'])
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|| FALLBACK_DATA.interviewerEvaluationTitle;
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const evaluationLabel = pickString(root, ['label', 'evaluation_label'])
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|| pickString(evaluation, ['label', 'evaluation_label'])
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|| FALLBACK_DATA.evaluationLabel;
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const selfScore = normalizeScore(
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pickNumber(root, ['candidate_score', 'self_score', 'self_rating'])
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?? pickNumber(evaluation, ['candidate_score', 'self_score', 'self_rating']),
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FALLBACK_DATA.selfScore,
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);
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const interviewerScore = normalizeScore(
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pickNumber(root, ['interviewer_score', 'score', 'interviewer_rating'])
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?? pickNumber(evaluation, ['interviewer_score', 'score', 'interviewer_rating']),
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FALLBACK_DATA.interviewerScore,
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);
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return {
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companyName,
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dateLabel,
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evaluationLabel,
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interviewerEvaluationBody,
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interviewerEvaluationLead,
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interviewerEvaluationTitle,
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interviewerScore,
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interviewTitle,
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recommendations: extractStringList(root, ['recommendations', 'constructive_recommendations', 'next_steps'], FALLBACK_RECOMMENDATIONS),
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selfScore,
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strengths: extractStringList(root, ['strengths', 'highlights'], FALLBACK_STRENGTHS),
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suggestions: extractSuggestions(root),
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};
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} catch {
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return {
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...FALLBACK_DATA,
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companyName: context?.companyName || FALLBACK_DATA.companyName,
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interviewTitle: context?.title || FALLBACK_DATA.interviewTitle,
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dateLabel: context?.dateLabel || FALLBACK_DATA.dateLabel,
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};
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}
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}
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async submitRating(interviewId: string, rating: number, comment: string): Promise<void> {
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await this.simulationService.submitEvaluationRating(interviewId, rating, comment);
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}
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}
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