feat: Zod AI validation, AIProvenance governance, fix tests (154 green)
- Add AIProvenance + AIResponse<T> to IAIService — all 11 methods now return structured provenance (provider, model, source, fallbackUsed, validationPassed) instead of bare ItemResponse<T> - Add schemas.ts with Zod schemas for all 8 AI response types; validateAIResponse() utility returns null on failure, never throws - Rewrite OpenRouterAIService: every method validates AI JSON against its Zod schema; failed validation triggers MockAIService fallback with fallbackUsed:true — no invalid data can reach the UI - Fix MockAIService.generateFollowUpQuestions: replace broken mockParseNeed(JSON.stringify(criteria)) with direct ParsedNeedCriteria field inspection; returns max 3 prioritised FollowUpQuestion objects - Add provenance: mockProvenance() to all MockAIService responses - Improve decisionBriefPrompt: structured JSON schema example, confidence vocabulary, availability disclaimer - Improve matchExplanationPrompt: score-tier vocabulary, isFutureSignal flag forbids confirmed-availability language for future signals - Add 102 new tests: mustHaveScorer (16), softFactorEnrichment (38), aiSchemas (52) — 154 total, all passing; 0 TypeScript errors Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Benjamin Sutter
@@ -1,9 +1,9 @@
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import type { ItemResponse } from '../../types'
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import type { CreateNeedInput } from '../../../domain/need'
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import type { ParsedNeedCriteria, FollowUpQuestion } from '../../../domain/needBuilder'
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import type { UnifiedMatchResult } from '../../../domain/unifiedResult'
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import type {
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IAIService,
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AIResponse,
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DecisionBrief,
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ComparisonSummary,
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CriteriaExtractionResult,
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@@ -16,6 +16,7 @@ import type {
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DataQualitySummary,
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MarketSignalClassification,
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} from '../IAIService'
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import { mockProvenance } from '../IAIService'
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import { mockParseNeed } from './needParser'
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import { buildComparisonSummary } from './compareBuilder'
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import { buildMockDecisionBrief } from './decisionBrief'
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@@ -23,19 +24,92 @@ import { buildMockDecisionBrief } from './decisionBrief'
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const SIMULATED_DELAY = { fast: 300, medium: 600, slow: 1800 }
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const delay = (ms: number) => new Promise(r => setTimeout(r, ms))
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// ── Follow-up question templates keyed by ParsedNeedCriteria field ────────────
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interface QuestionTemplate {
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questionText: string
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reason: string
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suggestedAnswerOptions?: string[]
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importance: FollowUpQuestion['importance']
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}
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const FOLLOW_UP_TEMPLATES: Partial<Record<keyof ParsedNeedCriteria, QuestionTemplate>> = {
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assetType: {
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questionText: 'Welchen Nutzungstyp suchen Sie?',
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reason: 'Nutzungstyp ist zwingend für die Matchsuche',
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suggestedAnswerOptions: ['Büro', 'Retail', 'Logistik', 'Produktion', 'Gastro'],
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importance: 'required',
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},
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areaRange: {
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questionText: 'Welche Fläche benötigen Sie (min–max in m²)?',
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reason: 'Flächenbedarf ist zwingend für die Filterung',
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importance: 'required',
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},
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preferredLocations: {
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questionText: 'In welchen Städten oder Regionen suchen Sie?',
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reason: 'Standortpräferenz fehlt',
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suggestedAnswerOptions: ['Zürich', 'Basel', 'Bern', 'Zug', 'Genf', 'Lausanne'],
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importance: 'required',
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},
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budgetRange: {
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questionText: 'Was ist Ihr maximales Budget pro m² und Monat (CHF)?',
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reason: 'Budget ist wichtig für die Filterung unpassender Objekte',
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importance: 'recommended',
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},
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timing: {
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questionText: 'Wann möchten Sie spätestens einziehen?',
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reason: 'Verfügbarkeitstermin fehlt',
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importance: 'recommended',
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},
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mustHaveCriteria: {
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questionText: 'Haben Sie zwingende Anforderungen (ÖV-Anbindung, Parkplätze, Laderampe)?',
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reason: 'Pflichtkriterien sind für die Filterung relevant',
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importance: 'optional',
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},
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}
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function buildFollowUpQuestions(criteria: ParsedNeedCriteria): FollowUpQuestion[] {
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const missing: Array<keyof ParsedNeedCriteria> = []
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if (!criteria.assetType) missing.push('assetType')
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if (!criteria.areaRange) missing.push('areaRange')
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if (!criteria.preferredLocations?.length) missing.push('preferredLocations')
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if (!criteria.budgetRange) missing.push('budgetRange')
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if (!criteria.timing) missing.push('timing')
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if (!criteria.mustHaveCriteria?.length) missing.push('mustHaveCriteria')
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return missing
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.slice(0, 3)
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.map((field, i) => {
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const tpl = FOLLOW_UP_TEMPLATES[field]
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if (!tpl) return null
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const q: FollowUpQuestion = {
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id: `fq-mock-${i}`,
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questionText: tpl.questionText,
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targetField: field,
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reason: tpl.reason,
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importance: tpl.importance,
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suggestedAnswerOptions: tpl.suggestedAnswerOptions,
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}
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return q
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})
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.filter((q): q is FollowUpQuestion => q !== null)
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}
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// ── Service ───────────────────────────────────────────────────────────────────
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export const MockAIService: IAIService = {
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async parseNeed(input: string): Promise<ItemResponse<ReturnType<typeof mockParseNeed>>> {
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async parseNeed(input: string): Promise<AIResponse<ReturnType<typeof mockParseNeed>>> {
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await delay(SIMULATED_DELAY.fast)
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return { data: mockParseNeed(input) }
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return { data: mockParseNeed(input), provenance: mockProvenance() }
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},
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async generateFollowUpQuestions(criteria: ParsedNeedCriteria): Promise<ItemResponse<FollowUpQuestion[]>> {
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async generateFollowUpQuestions(criteria: ParsedNeedCriteria): Promise<AIResponse<FollowUpQuestion[]>> {
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await delay(SIMULATED_DELAY.medium)
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const result = mockParseNeed(JSON.stringify(criteria))
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return { data: result.followUpQuestionCandidates }
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return { data: buildFollowUpQuestions(criteria), provenance: mockProvenance() }
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},
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async generateMatchExplanation(input: MatchExplanationInput): Promise<ItemResponse<MatchExplanation>> {
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async generateMatchExplanation(input: MatchExplanationInput): Promise<AIResponse<MatchExplanation>> {
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await delay(SIMULATED_DELAY.medium)
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const isStrong = input.matchScore >= 78
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const isMedium = input.matchScore >= 52
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@@ -56,10 +130,11 @@ export const MockAIService: IAIService = {
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...input.negativeFactors.slice(0, 1).map(f => `− ${f.explanation}`),
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],
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},
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provenance: mockProvenance(),
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}
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},
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async summarizeTradeOffs(tradeoffs: TradeOffInput[]): Promise<ItemResponse<TradeOffSummary>> {
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async summarizeTradeOffs(tradeoffs: TradeOffInput[]): Promise<AIResponse<TradeOffSummary>> {
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await delay(SIMULATED_DELAY.fast)
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const critical = tradeoffs.filter(t => t.severity === 'HIGH')
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const overallRisk: TradeOffSummary['overallRisk'] =
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@@ -73,20 +148,21 @@ export const MockAIService: IAIService = {
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items: tradeoffs.map(t => ({ concern: t.concern, severity: t.severity, mitigation: t.mitigation })),
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overallRisk,
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},
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provenance: mockProvenance(),
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}
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},
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async summarizeComparison(items: UnifiedMatchResult[]): Promise<ItemResponse<ComparisonSummary>> {
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async summarizeComparison(items: UnifiedMatchResult[]): Promise<AIResponse<ComparisonSummary>> {
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await delay(SIMULATED_DELAY.medium)
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return { data: buildComparisonSummary(items) }
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return { data: buildComparisonSummary(items), provenance: mockProvenance() }
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},
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async generateDecisionBrief(shortlistId: string): Promise<ItemResponse<DecisionBrief>> {
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async generateDecisionBrief(shortlistId: string): Promise<AIResponse<DecisionBrief>> {
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await delay(SIMULATED_DELAY.slow)
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return { data: buildMockDecisionBrief(shortlistId) }
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return { data: buildMockDecisionBrief(shortlistId), provenance: mockProvenance() }
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},
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async generateDataQualitySummary(_propertyId: string, quality: DataQualityInput): Promise<ItemResponse<DataQualitySummary>> {
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async generateDataQualitySummary(_propertyId: string, quality: DataQualityInput): Promise<AIResponse<DataQualitySummary>> {
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await delay(SIMULATED_DELAY.fast)
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const level =
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quality.score >= 0.85 ? 'excellent'
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@@ -113,10 +189,11 @@ export const MockAIService: IAIService = {
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: 'Keine sofortigen Massnahmen erforderlich.',
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confidence: quality.score,
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},
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provenance: mockProvenance(),
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}
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},
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async classifyMarketSignal(signalText: string): Promise<ItemResponse<MarketSignalClassification>> {
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async classifyMarketSignal(signalText: string): Promise<AIResponse<MarketSignalClassification>> {
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await delay(SIMULATED_DELAY.medium)
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const t = signalText.toLowerCase()
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let signalType: MarketSignalClassification['signalType'] = 'UNKNOWN'
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@@ -136,10 +213,11 @@ export const MockAIService: IAIService = {
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credibility: 'MEDIUM',
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reasoning: `Keyword-basierte Klassifikation (Mock). Signaltyp: ${signalType}.`,
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},
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provenance: mockProvenance(),
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}
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},
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async generateOfferEmail(payload: OfferEmailPayload): Promise<ItemResponse<{ subject: string; body: string }>> {
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async generateOfferEmail(payload: OfferEmailPayload): Promise<AIResponse<{ subject: string; body: string }>> {
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await delay(SIMULATED_DELAY.medium * 2)
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return {
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data: {
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@@ -149,11 +227,12 @@ export const MockAIService: IAIService = {
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payload.properties.map((p, i) => `• ${p} (Match-Score: ${payload.matchScores[i]}%)`).join('\n') +
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`\n\nGerne arrangieren wir Besichtigungstermine für die genannten Objekte und stehen für alle weiteren Fragen zur Verfügung.\n\nFreundliche Grüsse\nWincasa AG`,
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},
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provenance: mockProvenance(),
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}
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},
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// Legacy methods
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async extractCriteria(_input: string): Promise<ItemResponse<CriteriaExtractionResult>> {
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async extractCriteria(_input: string): Promise<AIResponse<CriteriaExtractionResult>> {
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return {
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data: {
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extractedCriteria: {
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@@ -170,15 +249,16 @@ export const MockAIService: IAIService = {
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'Wann möchten Sie spätestens einziehen?',
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],
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},
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provenance: mockProvenance(),
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}
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},
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async generateFollowUp(partialNeed: Partial<CreateNeedInput>): Promise<ItemResponse<string[]>> {
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async generateFollowUp(partialNeed: Partial<CreateNeedInput>): Promise<AIResponse<string[]>> {
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const questions: string[] = []
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if (!partialNeed.assetType) questions.push('Welchen Nutzungstyp suchen Sie?')
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if (!partialNeed.preferredLocations?.length) questions.push('In welchen Regionen suchen Sie?')
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if (!partialNeed.timing) questions.push('Was ist Ihr gewünschter Einzugstermin?')
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if (!partialNeed.budgetRange) questions.push('Was ist Ihr maximales monatliches Budget?')
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return { data: questions }
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return { data: questions, provenance: mockProvenance() }
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},
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}
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