feat: F008 AI need builder — smart parse, criteria review, follow-up & weighting
Domain: ParsedNeedCriteria, FollowUpQuestion, ParseNeedResult, NeedBuilderStep, WEIGHTING_KEYS/LABELS. Services: weightingService (asset-type profiles), aiService extended with parseNeed (keyword extraction mock, 1.4s delay) and generateFollowUpQuestions. Components: NeedBuilderProgress, NeedInput, ConfidenceFieldBadge, ExtractedFieldRow, CriteriaReviewPanel, FollowUpQuestionCard, FollowUpPanel, WeightingEditor, NeedCardPreview, NeedBuilderErrorState. Page: AINeedBuilderPage replaces AISearch with 4-step flow (input → review → weighting → save). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Benjamin Sutter
+227
-2
@@ -1,6 +1,10 @@
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import type { ItemResponse, ServiceError } from './types'
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import { ServiceErrorCode } from './types'
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import type { CreateNeedInput } from '../domain/need'
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import type { AssetType } from '../domain/enums'
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import type { ParseNeedResult, ParsedNeedCriteria, FollowUpQuestion } from '../domain/needBuilder'
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// ── Legacy types (kept for backward compatibility) ────────────────────────────
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export interface CriteriaExtractionResult {
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extractedCriteria: Partial<CreateNeedInput>
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@@ -15,9 +19,218 @@ export interface AIServiceProvider {
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generateFollowUp(partialNeed: Partial<CreateNeedInput>): Promise<string[]>
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}
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// ── Mock parse logic ──────────────────────────────────────────────────────────
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function mockParseNeed(input: string): ParseNeedResult {
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const lower = input.toLowerCase()
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// Asset type
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const assetType: AssetType | undefined =
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lower.includes('büro') || lower.includes('office') ? 'OFFICE'
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: lower.includes('logistik') || lower.includes('lager') ? 'LOGISTICS'
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: lower.includes('retail') || lower.includes('laden') || lower.includes('shop') ? 'RETAIL'
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: lower.includes('produktion') || lower.includes('gewerbe') || lower.includes('industrie') ? 'PRODUCTION'
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: lower.includes('gastro') || lower.includes('restaurant') ? 'GASTRO'
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: undefined
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// Area
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const areaRangeMatch = input.match(/(\d+)\s*[–\-–]\s*(\d+)\s*m[²2]/i)
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const areaSingleMatch = input.match(/(\d{3,5})\s*m[²2]/i)
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let areaRange: { min: number; max: number } | undefined
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let areaConfidence = 0.25
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if (areaRangeMatch) {
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areaRange = { min: parseInt(areaRangeMatch[1]), max: parseInt(areaRangeMatch[2]) }
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areaConfidence = 0.95
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} else if (areaSingleMatch) {
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const base = parseInt(areaSingleMatch[1])
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areaRange = { min: Math.round(base * 0.8), max: Math.round(base * 1.2) }
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areaConfidence = 0.70
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}
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// Locations
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const CITIES: [string, string][] = [
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['zürich', 'Zürich'], ['basel', 'Basel'], ['bern', 'Bern'], ['genf', 'Genf'],
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['lausanne', 'Lausanne'], ['winterthur', 'Winterthur'], ['zug', 'Zug'],
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['luzern', 'Luzern'], ['st. gallen', 'St. Gallen'], ['lugano', 'Lugano'],
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['biel', 'Biel'], ['schaffhausen', 'Schaffhausen'],
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]
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const preferredLocations = CITIES.filter(([k]) => lower.includes(k)).map(([, v]) => v)
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const locationConfidence = preferredLocations.length > 0 ? 0.88 : 0.15
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// Budget
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const budgetPerSqmMatch = input.match(/(\d+)\s*(?:CHF)?\s*\/\s*m[²2]/i)
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const budgetMaxMatch = input.match(/(?:max\.?|bis|höchstens)\s*(?:CHF\s*)?(\d+)/i)
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let budgetRange: { maxPerSqm: number; currency: string } | undefined
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let budgetConfidence = 0.20
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if (budgetPerSqmMatch) {
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budgetRange = { maxPerSqm: parseInt(budgetPerSqmMatch[1]), currency: 'CHF' }
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budgetConfidence = 0.92
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} else if (budgetMaxMatch) {
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budgetRange = { maxPerSqm: parseInt(budgetMaxMatch[1]), currency: 'CHF' }
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budgetConfidence = 0.60
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}
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// Timing
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const yearMatch = input.match(/(?:ab\s+)?(?:Q[1-4]\s*\/?\s*)?(\d{4})/)
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const soonMatch = lower.includes('sofort') || lower.includes('asap')
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let timing: ParsedNeedCriteria['timing'] | undefined
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let timingConfidence = 0.20
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if (soonMatch) {
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timing = { earliestMoveIn: '2025-07-01', latestMoveIn: '2025-10-01', flexibleTiming: false }
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timingConfidence = 0.85
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} else if (yearMatch) {
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timing = { earliestMoveIn: `${yearMatch[1]}-01-01`, latestMoveIn: `${yearMatch[1]}-12-31`, flexibleTiming: lower.includes('flexibel') }
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timingConfidence = 0.75
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}
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// Must-haves
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const mustHaveCriteria: string[] = []
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if (lower.includes('öv') || lower.includes('bahnhof') || lower.includes('tram')) mustHaveCriteria.push('Gute ÖV-Anbindung')
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if (lower.includes('parking') || lower.includes('parkplatz') || lower.includes('tiefgarage')) mustHaveCriteria.push('Parkplätze vorhanden')
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if (lower.includes('klimaanlage') || lower.includes('klima')) mustHaveCriteria.push('Klimaanlage')
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if (lower.includes('server') || lower.includes('rechenzentr')) mustHaveCriteria.push('Serverraum / IT-Infrastruktur')
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if (lower.includes('barrierefrei')) mustHaveCriteria.push('Barrierefreiheit')
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if (lower.includes('küche') || lower.includes('kantine')) mustHaveCriteria.push('Kantine / Küche')
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// Soft
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const prestigeImportance: 'LOW' | 'MEDIUM' | 'HIGH' | undefined =
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lower.includes('prestige') || lower.includes('representativ') || lower.includes('repräsentativ') ? 'HIGH'
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: lower.includes('standard') ? 'LOW'
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: undefined
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const parkingNeed = lower.includes('parking') || lower.includes('parkplatz')
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const visibilityNeed: 'HIGH' | undefined = lower.includes('sichtbar') || lower.includes('passanten') ? 'HIGH' : undefined
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const footfallNeed: 'HIGH' | undefined = lower.includes('frequenz') || lower.includes('laufkundschaft') ? 'HIGH' : undefined
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// Missing fields
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const missingFields: string[] = []
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if (!assetType) missingFields.push('Nutzungstyp')
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if (!areaRange) missingFields.push('Flächenbedarf')
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if (preferredLocations.length === 0) missingFields.push('Standort')
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if (!budgetRange) missingFields.push('Budget')
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if (!timing) missingFields.push('Verfügbarkeitstermin')
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// Assumptions
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const assumptions: string[] = []
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if (areaRange && areaSingleMatch && !areaRangeMatch) {
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assumptions.push(`Flächenrange aus Einzelangabe (${areaSingleMatch[1]} m²) geschätzt — bitte prüfen`)
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}
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if (budgetRange && !budgetPerSqmMatch && budgetMaxMatch) {
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assumptions.push('Budget als Pauschalangabe interpretiert — Angabe pro m² unklar')
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}
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if (!assetType) {
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assumptions.push('Nutzungstyp konnte nicht eindeutig erkannt werden')
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}
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// Confidence by field
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const confidenceByField: Record<string, number> = {
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assetType: assetType ? 0.92 : 0.20,
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areaRange: areaConfidence,
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preferredLocations: locationConfidence,
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budgetRange: budgetConfidence,
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timing: timingConfidence,
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mustHaveCriteria: mustHaveCriteria.length > 0 ? 0.85 : 0.10,
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prestigeImportance: prestigeImportance ? 0.80 : 0.20,
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parkingNeed: parkingNeed ? 0.90 : 0.30,
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}
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// Follow-up questions
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const followUpQuestionCandidates: FollowUpQuestion[] = []
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if (!assetType) {
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followUpQuestionCandidates.push({
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id: 'fq-asset-type',
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questionText: 'Welchen Nutzungstyp suchen Sie?',
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targetField: 'assetType',
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reason: 'Der Nutzungstyp konnte nicht eindeutig erkannt werden.',
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suggestedAnswerOptions: ['Büro', 'Logistik / Lager', 'Retail', 'Produktion', 'Gastro / F&B'],
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importance: 'required',
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})
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}
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if (preferredLocations.length === 0) {
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followUpQuestionCandidates.push({
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id: 'fq-location',
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questionText: 'In welcher Region oder Stadt suchen Sie?',
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targetField: 'preferredLocations',
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reason: 'Kein konkreter Standort angegeben.',
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suggestedAnswerOptions: ['Zürich', 'Basel', 'Bern', 'Zug', 'Luzern', 'Genf'],
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importance: 'required',
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})
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}
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if (!timing) {
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followUpQuestionCandidates.push({
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id: 'fq-timing',
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questionText: 'Ab wann benötigen Sie die Fläche?',
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targetField: 'timing',
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reason: 'Kein Verfügbarkeitsdatum erkannt.',
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suggestedAnswerOptions: ['Sofort', 'In 3 Monaten', 'In 6 Monaten', 'In 12 Monaten', 'Flexibel'],
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importance: 'recommended',
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})
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}
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if (!budgetRange) {
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followUpQuestionCandidates.push({
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id: 'fq-budget',
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questionText: 'Was ist Ihr Maximalbudget pro m² und Jahr?',
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targetField: 'budgetRange',
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reason: 'Kein Budget erkannt.',
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suggestedAnswerOptions: ['< CHF 20/m²', 'CHF 20–40/m²', 'CHF 40–80/m²', '> CHF 80/m²', 'Flexible'],
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importance: 'recommended',
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})
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}
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followUpQuestionCandidates.push({
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id: 'fq-parking',
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questionText: 'Benötigen Sie Parkplätze vor Ort?',
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targetField: 'parkingNeed',
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reason: 'Angabe zu Parkplatzbedarf verbessert die Matchqualität.',
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suggestedAnswerOptions: ['Ja, zwingend', 'Ja, wenn möglich', 'Nein'],
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importance: 'optional',
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})
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// Suggested weights
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const suggestedWeights: Record<string, number> = {
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area: 0.20,
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location: preferredLocations.length > 0 ? 0.28 : 0.22,
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budget: budgetRange ? 0.22 : 0.18,
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timing: timing ? 0.15 : 0.12,
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prestige: prestigeImportance === 'HIGH' ? 0.10 : 0.05,
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accessibility: mustHaveCriteria.includes('Gute ÖV-Anbindung') ? 0.08 : 0.04,
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expansionPotential: 0.03,
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flexibility: lower.includes('flexibel') ? 0.07 : 0.03,
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}
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const rawSummary = `Bedarf analysiert: ${assetType ?? 'Typ unbekannt'} · ${preferredLocations.join(', ') || 'Standort unklar'} · ${areaRange ? `${areaRange.min}–${areaRange.max} m²` : 'Fläche unklar'} · ${budgetRange ? `max. CHF ${budgetRange.maxPerSqm}/m²` : 'Budget unklar'}`
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return {
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extractedCriteria: {
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assetType,
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areaRange,
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preferredLocations,
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budgetRange,
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timing,
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mustHaveCriteria,
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infrastructureRequirements: [],
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accessibilityRequirements: mustHaveCriteria.includes('Gute ÖV-Anbindung') ? ['ÖV-Anbindung'] : [],
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prestigeImportance,
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flexibilityNeed: lower.includes('flexibel') ? 'HIGH' : 'MEDIUM',
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expansionPotential: lower.includes('wachstum') || lower.includes('expansion'),
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parkingNeed,
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visibilityNeed,
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footfallNeed,
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},
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confidenceByField,
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missingFields,
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assumptions,
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suggestedWeights,
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followUpQuestionCandidates,
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rawSummary,
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promptVersion: 'mock-v1.0',
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schemaVersion: '1.0.0',
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}
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}
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// ── Legacy mock provider (kept for backward compat) ───────────────────────────
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const MockupAIServiceProvider: AIServiceProvider = {
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async extractCriteria(_input: string): Promise<CriteriaExtractionResult> {
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// Deterministic mock extraction — simulates AI parsing
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return {
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extractedCriteria: {
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companyName: 'Unbekannt (bitte bestätigen)',
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@@ -51,7 +264,6 @@ const notConfiguredError = (): ServiceError => ({
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message: 'OpenRouter nicht konfiguriert',
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})
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// Stub — swap for real OpenRouter implementation without changing call sites
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export const openRouterAIService: AIServiceProvider = {
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async extractCriteria(_input: string): Promise<CriteriaExtractionResult> {
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throw notConfiguredError()
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@@ -62,6 +274,7 @@ export const openRouterAIService: AIServiceProvider = {
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}
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export const aiService = {
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// Legacy methods
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async extractCriteria(input: string): Promise<ItemResponse<CriteriaExtractionResult>> {
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const data = await provider.extractCriteria(input)
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return { data }
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@@ -70,4 +283,16 @@ export const aiService = {
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const data = await provider.generateFollowUp(partialNeed)
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return { data }
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},
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// F008 methods
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async parseNeed(input: string): Promise<ItemResponse<ParseNeedResult>> {
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await new Promise(r => setTimeout(r, 1400))
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const data = mockParseNeed(input)
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return { data }
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},
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async generateFollowUpQuestions(criteria: ParsedNeedCriteria): Promise<ItemResponse<FollowUpQuestion[]>> {
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await new Promise(r => setTimeout(r, 600))
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const result = mockParseNeed(JSON.stringify(criteria))
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return { data: result.followUpQuestionCandidates }
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},
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}
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@@ -0,0 +1,32 @@
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import type { WeightingKey } from '../domain/needBuilder'
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type WeightProfile = Record<WeightingKey, number>
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const PROFILES: Record<string, WeightProfile> = {
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OFFICE: {
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area: 0.20, location: 0.25, budget: 0.20, timing: 0.15,
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prestige: 0.10, accessibility: 0.05, expansionPotential: 0.03, flexibility: 0.02,
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},
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LOGISTICS: {
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area: 0.30, location: 0.20, budget: 0.20, timing: 0.15,
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prestige: 0.02, accessibility: 0.08, expansionPotential: 0.03, flexibility: 0.02,
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},
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RETAIL: {
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area: 0.15, location: 0.30, budget: 0.20, timing: 0.10,
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prestige: 0.12, accessibility: 0.08, expansionPotential: 0.03, flexibility: 0.02,
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},
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PRODUCTION: {
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area: 0.30, location: 0.20, budget: 0.20, timing: 0.15,
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prestige: 0.02, accessibility: 0.07, expansionPotential: 0.04, flexibility: 0.02,
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},
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DEFAULT: {
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area: 0.25, location: 0.25, budget: 0.20, timing: 0.15,
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prestige: 0.07, accessibility: 0.05, expansionPotential: 0.02, flexibility: 0.01,
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},
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}
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export const weightingService = {
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getDefaultWeights(assetType?: string): WeightProfile {
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return { ...(PROFILES[assetType ?? 'DEFAULT'] ?? PROFILES.DEFAULT) }
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},
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}
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