Benjamin Sutter
e62391af66
- 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>
550 lines
26 KiB
TypeScript
550 lines
26 KiB
TypeScript
/**
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* OpenRouter AI Service
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*
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* Activation:
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* VITE_AI_PROVIDER=openrouter
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* VITE_OPENROUTER_API_KEY=<your-key>
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* VITE_OPENROUTER_MODEL=anthropic/claude-3-5-haiku (optional, default shown)
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*
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* Every method follows this contract:
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* 1. No API key → warn + MockAIService fallback (fallbackUsed: true)
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* 2. HTTP error → error log + MockAIService fallback
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* 3. JSON parse fail → warn + MockAIService fallback
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* 4. Zod schema fail → warn + MockAIService fallback ← NEW
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* 5. Success (full AI) → AI response, source: 'ai', validationPassed: true
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* 6. Hybrid → source: 'hybrid', documented per-method
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*
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* No invalid data ever reaches the UI.
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*/
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import type { CreateNeedInput } from '../../../domain/need'
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import type { ParseNeedResult, ParsedNeedCriteria, FollowUpQuestion } from '../../../domain/needBuilder'
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import type { UnifiedMatchResult } from '../../../domain/unifiedResult'
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import type { AssetType } from '../../../domain/enums'
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import type {
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IAIService,
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AIResponse,
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AIProvenance,
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DecisionBrief,
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ComparisonSummary,
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CriteriaExtractionResult,
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OfferEmailPayload,
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MatchExplanationInput,
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MatchExplanation,
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TradeOffInput,
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TradeOffSummary,
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DataQualityInput,
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DataQualitySummary,
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MarketSignalClassification,
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} from '../IAIService'
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import { ServiceErrorCode } from '../../types'
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import { AppError } from '../../errors'
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import {
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NeedParsingResponseSchema,
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FollowUpQuestionsResponseSchema,
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TradeOffSummaryResponseSchema,
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CompareSummaryResponseSchema,
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DecisionBriefResponseSchema,
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DataQualitySummaryResponseSchema,
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MarketSignalClassificationResponseSchema,
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OfferEmailResponseSchema,
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validateAIResponse,
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} from '../schemas'
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import { buildNeedParsingPrompt } from '../prompts/needParsingPrompt'
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import { buildFollowUpQuestionsPrompt } from '../prompts/followUpQuestionsPrompt'
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import { buildMatchExplanationPrompt } from '../prompts/matchExplanationPrompt'
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import { buildTradeOffPrompt } from '../prompts/tradeOffPrompt'
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import { buildCompareSummaryPrompt } from '../prompts/compareSummaryPrompt'
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import { buildDecisionBriefPrompt } from '../prompts/decisionBriefPrompt'
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import { buildDataQualityPrompt } from '../prompts/dataQualityPrompt'
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import { buildMarketSignalPrompt } from '../prompts/marketSignalPrompt'
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import { MockAIService } from '../mock/MockAIService'
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// ── Config ────────────────────────────────────────────────────────────────────
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const API_BASE = 'https://openrouter.ai/api/v1'
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const DEFAULT_MODEL = 'anthropic/claude-3-5-haiku'
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const PROMPT_VERSION = 'v1.1'
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const SCHEMA_VERSION = 'v1.0'
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interface OpenRouterConfig {
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apiKey: string
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model: string
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}
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function getConfig(): OpenRouterConfig | null {
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const apiKey = import.meta.env.VITE_OPENROUTER_API_KEY as string | undefined
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if (!apiKey) return null
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return {
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apiKey,
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model: (import.meta.env.VITE_OPENROUTER_MODEL as string | undefined) ?? DEFAULT_MODEL,
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}
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}
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function makeProvenance(
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config: OpenRouterConfig,
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source: AIProvenance['source'],
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fallbackUsed: boolean,
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validationPassed: boolean,
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): AIProvenance {
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return {
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provider: 'openrouter',
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model: config.model,
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generatedAt: new Date().toISOString(),
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promptVersion: PROMPT_VERSION,
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source,
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fallbackUsed,
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validationPassed,
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}
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}
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// ── HTTP helper ───────────────────────────────────────────────────────────────
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async function chat(config: OpenRouterConfig, system: string, user: string): Promise<string> {
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const res = await fetch(`${API_BASE}/chat/completions`, {
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method: 'POST',
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headers: {
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'Authorization': `Bearer ${config.apiKey}`,
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'Content-Type': 'application/json',
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'HTTP-Referer': window.location.origin,
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},
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body: JSON.stringify({
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model: config.model,
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messages: [
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{ role: 'system', content: system },
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{ role: 'user', content: user },
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],
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}),
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})
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if (!res.ok) {
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const body = await res.text()
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throw new AppError({
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code: ServiceErrorCode.AI_GENERATION_FAILED,
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message: `OpenRouter error ${res.status}: ${body}`,
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})
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}
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const json = await res.json() as { choices: Array<{ message: { content: string } }> }
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return json.choices[0]?.message?.content ?? ''
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}
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// ── JSON extraction ───────────────────────────────────────────────────────────
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function extractJSON<T>(raw: string): T | null {
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const fenced = raw.match(/```(?:json)?\s*\n?([\s\S]*?)\n?```/)
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const candidate = fenced ? fenced[1] : raw.match(/([\[{][\s\S]*[\]}])/)?.[1] ?? raw
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try {
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return JSON.parse(candidate) as T
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} catch {
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return null
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}
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}
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// ── ParseNeed helpers ─────────────────────────────────────────────────────────
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type RawNeedParseAI = {
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assetType?: string | null
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areaRange?: { min: number; max: number } | null
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preferredLocations?: string[]
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budgetRange?: { maxPerSqm: number; currency: string } | null
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timing?: { earliestMoveIn: string; latestMoveIn?: string; flexibleTiming: boolean } | null
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mustHaveCriteria?: string[]
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missingFields?: string[]
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assumptions?: string[]
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}
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function followUpForField(field: string): string {
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const MAP: Record<string, string> = {
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assetType: 'Welchen Nutzungstyp suchen Sie (Büro, Retail, Logistik, Produktion)?',
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areaRange: 'Welche Fläche benötigen Sie (min–max in m²)?',
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preferredLocations: 'In welchen Städten oder Regionen suchen Sie?',
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budgetRange: 'Was ist Ihr maximales Budget pro m² und Jahr?',
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timing: 'Wann möchten Sie spätestens einziehen?',
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mustHaveCriteria: 'Haben Sie zwingende Anforderungen (ÖV-Anbindung, Parkplätze, Laderampe)?',
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}
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return MAP[field] ?? `Können Sie "${field}" präzisieren?`
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}
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function defaultSuggestedWeights(): Record<string, number> {
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return {
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area: 0.25, location: 0.20, budget: 0.20, timing: 0.15,
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prestige: 0.05, accessibility: 0.05, expansionPotential: 0.02,
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flexibility: 0.02, visibility: 0.02, footfall: 0.01, talentAccess: 0.01,
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esg: 0.01, taxEnvironment: 0.01,
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}
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}
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// ── Fallback wrapper ──────────────────────────────────────────────────────────
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type FallbackFn<T> = () => Promise<AIResponse<T>>
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async function withFallback<T>(
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label: string,
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fn: (config: OpenRouterConfig) => Promise<AIResponse<T>>,
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fallback: FallbackFn<T>,
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): Promise<AIResponse<T>> {
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const config = getConfig()
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if (!config) {
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console.warn(`[OpenRouterAIService] ${label}: no API key — using MockAIService`)
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const result = await fallback()
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return { ...result, provenance: { ...result.provenance, fallbackUsed: true } }
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}
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try {
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return await fn(config)
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} catch (err) {
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console.error(`[OpenRouterAIService] ${label} failed:`, err)
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const result = await fallback()
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return { ...result, provenance: { ...result.provenance, fallbackUsed: true } }
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}
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}
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// ── Service ───────────────────────────────────────────────────────────────────
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export const OpenRouterAIService: IAIService = {
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// ── parseNeed ───────────────────────────────────────────────────────────────
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parseNeed(input: string): Promise<AIResponse<ParseNeedResult>> {
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return withFallback('parseNeed', async (config) => {
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const { system, user } = buildNeedParsingPrompt({ userInput: input })
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const raw = await chat(config, system, user)
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const json = extractJSON<RawNeedParseAI>(raw)
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const ai = json ? validateAIResponse(NeedParsingResponseSchema, json, 'parseNeed') : null
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if (!ai) {
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console.warn('[OpenRouterAIService] parseNeed: invalid response — using mock fallback')
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const fb = await MockAIService.parseNeed(input)
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return { ...fb, provenance: makeProvenance(config, 'mock', true, false) }
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}
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const extractedCriteria: ParsedNeedCriteria = {
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assetType: (ai.assetType ?? undefined) as AssetType | undefined,
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areaRange: ai.areaRange ?? undefined,
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preferredLocations: ai.preferredLocations,
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budgetRange: ai.budgetRange ?? undefined,
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timing: ai.timing
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? { ...ai.timing, latestMoveIn: ai.timing.latestMoveIn ?? undefined }
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: undefined,
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mustHaveCriteria: ai.mustHaveCriteria,
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}
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const missingFields = ai.missingFields ?? []
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const confidenceByField: Record<string, number> = {}
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Object.keys(extractedCriteria).forEach(k => {
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confidenceByField[k] = extractedCriteria[k as keyof ParsedNeedCriteria] != null ? 0.85 : 0
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})
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missingFields.forEach(f => { confidenceByField[f] = 0 })
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const followUpQuestionCandidates: FollowUpQuestion[] = missingFields.map((field, i) => ({
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id: `fq-or-${i}`,
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questionText: followUpForField(field),
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targetField: field,
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reason: `Feld "${field}" nicht im Text erkannt`,
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importance: 'recommended' as const,
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}))
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return {
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data: {
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extractedCriteria,
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confidenceByField,
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missingFields,
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assumptions: ai.assumptions ?? [],
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suggestedWeights: defaultSuggestedWeights(),
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followUpQuestionCandidates,
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rawSummary: raw.substring(0, 500),
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promptVersion: PROMPT_VERSION,
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schemaVersion: SCHEMA_VERSION,
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},
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provenance: makeProvenance(config, 'ai', false, true),
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}
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}, () => MockAIService.parseNeed(input))
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},
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// ── generateFollowUpQuestions ───────────────────────────────────────────────
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generateFollowUpQuestions(criteria: ParsedNeedCriteria): Promise<AIResponse<FollowUpQuestion[]>> {
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return withFallback('generateFollowUpQuestions', async (config) => {
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const missingFields = Object.entries(criteria)
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.filter(([, v]) => v == null)
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.map(([k]) => k)
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const { system, user } = buildFollowUpQuestionsPrompt({ criteria, missingFields })
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const raw = await chat(config, system, user)
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const json = extractJSON<unknown[]>(raw)
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const ai = json ? validateAIResponse(FollowUpQuestionsResponseSchema, json, 'generateFollowUpQuestions') : null
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if (!ai?.length) {
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console.warn('[OpenRouterAIService] generateFollowUpQuestions: invalid response — using mock fallback')
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const fb = await MockAIService.generateFollowUpQuestions(criteria)
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return { ...fb, provenance: makeProvenance(config, 'mock', true, false) }
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}
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return {
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data: ai.map((q, i) => ({
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id: `fq-or-${i}`,
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questionText: q.questionText,
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targetField: q.targetField,
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reason: q.reason ?? 'AI-generiert',
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suggestedAnswerOptions: q.suggestedAnswerOptions,
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importance: (q.importance ?? 'recommended') as FollowUpQuestion['importance'],
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})),
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provenance: makeProvenance(config, 'ai', false, true),
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}
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}, () => MockAIService.generateFollowUpQuestions(criteria))
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},
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// ── generateMatchExplanation ────────────────────────────────────────────────
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// Plain-text response — no JSON schema to validate, but non-empty check enforced.
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generateMatchExplanation(input: MatchExplanationInput): Promise<AIResponse<MatchExplanation>> {
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return withFallback('generateMatchExplanation', async (config) => {
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const { system, user } = buildMatchExplanationPrompt(input)
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const raw = await chat(config, system, user)
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const summary = raw.trim()
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if (!summary) {
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console.warn('[OpenRouterAIService] generateMatchExplanation: empty response — using mock fallback')
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const fb = await MockAIService.generateMatchExplanation(input)
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return { ...fb, provenance: makeProvenance(config, 'mock', true, false) }
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}
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const scoreLabel = input.matchScore >= 78 ? 'Starkes' : input.matchScore >= 52 ? 'Gutes' : 'Schwaches'
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return {
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data: {
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headline: `${scoreLabel} Match — ${input.propertyTitle} (${input.matchScore}/100)`,
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summary,
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keyReasons: [
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...input.positiveFactors.slice(0, 2).map(f => `+ ${f.explanation}`),
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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: makeProvenance(config, 'ai', false, true),
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}
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}, () => MockAIService.generateMatchExplanation(input))
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},
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// ── summarizeTradeOffs ──────────────────────────────────────────────────────
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summarizeTradeOffs(tradeoffs: TradeOffInput[]): Promise<AIResponse<TradeOffSummary>> {
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return withFallback('summarizeTradeOffs', async (config) => {
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const { system, user } = buildTradeOffPrompt(tradeoffs, 'Objekt')
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const raw = await chat(config, system, user)
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const json = extractJSON<unknown>(raw)
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const ai = json ? validateAIResponse(TradeOffSummaryResponseSchema, json, 'summarizeTradeOffs') : null
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if (!ai) {
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console.warn('[OpenRouterAIService] summarizeTradeOffs: invalid response — using mock fallback')
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const fb = await MockAIService.summarizeTradeOffs(tradeoffs)
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return { ...fb, provenance: makeProvenance(config, 'mock', true, false) }
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}
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return {
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data: {
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headline: ai.headline,
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items: ai.items.map(item => ({
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concern: item.concern,
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severity: item.severity,
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mitigation: item.mitigation,
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})),
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overallRisk: ai.overallRisk,
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},
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provenance: makeProvenance(config, 'ai', false, true),
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}
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}, () => MockAIService.summarizeTradeOffs(tradeoffs))
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},
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// ── summarizeComparison ─────────────────────────────────────────────────────
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// Hybrid: AI provides narrative text; mock provides structural per-property data.
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// source: 'hybrid' — both are labeled in provenance.
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summarizeComparison(items: UnifiedMatchResult[]): Promise<AIResponse<ComparisonSummary>> {
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return withFallback('summarizeComparison', async (config) => {
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type ItemWithProp = UnifiedMatchResult & {
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property?: { title?: string; location?: { city?: string }; rentPricePerSqm?: number }
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}
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const properties = (items as ItemWithProp[])
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.filter(i => i.resultType !== 'FUTURE_AVAILABILITY')
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.map(i => ({
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title: i.property?.title ?? `Match ${i.matchScore}`,
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matchScore: i.matchScore,
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city: i.property?.location?.city ?? '–',
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rentPerSqm: i.property?.rentPricePerSqm ?? 0,
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positiveFactors: i.match.positiveFactors.slice(0, 2).map(f => f.explanation ?? f.criterion),
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negativeFactors: i.match.negativeFactors.slice(0, 2).map(f => f.explanation ?? f.criterion),
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}))
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const { system, user } = buildCompareSummaryPrompt({ properties })
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const raw = await chat(config, system, user)
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const json = extractJSON<unknown>(raw)
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const ai = json ? validateAIResponse(CompareSummaryResponseSchema, json, 'summarizeComparison') : null
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if (!ai) {
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console.warn('[OpenRouterAIService] summarizeComparison: invalid response — using mock fallback')
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const fb = await MockAIService.summarizeComparison(items)
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return { ...fb, provenance: makeProvenance(config, 'mock', true, false) }
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}
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const mock = await MockAIService.summarizeComparison(items)
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return {
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data: {
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...mock.data,
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overallAssessment: ai.overallAssessment,
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recommendation: ai.recommendation ?? mock.data.recommendation,
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},
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provenance: makeProvenance(config, 'hybrid', false, true),
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}
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}, () => MockAIService.summarizeComparison(items))
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},
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// ── generateDecisionBrief ───────────────────────────────────────────────────
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// Hybrid: AI generates narrative summary + sections; mock fills structural metadata.
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generateDecisionBrief(shortlistId: string): Promise<AIResponse<DecisionBrief>> {
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return withFallback('generateDecisionBrief', async (config) => {
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const { system, user } = buildDecisionBriefPrompt({ shortlistItems: [], needSummary: shortlistId })
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const raw = await chat(config, system, user)
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const json = extractJSON<unknown>(raw)
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const ai = json ? validateAIResponse(DecisionBriefResponseSchema, json, 'generateDecisionBrief') : null
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if (!ai) {
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console.warn('[OpenRouterAIService] generateDecisionBrief: invalid response — using mock fallback')
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const fb = await MockAIService.generateDecisionBrief(shortlistId)
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return { ...fb, provenance: makeProvenance(config, 'mock', true, false) }
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}
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const mock = await MockAIService.generateDecisionBrief(shortlistId)
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return {
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data: {
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...mock.data,
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summary: ai.summary,
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sections: ai.sections.map(s => ({ title: s.title, body: s.body })),
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},
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provenance: makeProvenance(config, 'hybrid', false, true),
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}
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}, () => MockAIService.generateDecisionBrief(shortlistId))
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},
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// ── generateDataQualitySummary ──────────────────────────────────────────────
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generateDataQualitySummary(propertyId: string, quality: DataQualityInput): Promise<AIResponse<DataQualitySummary>> {
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return withFallback('generateDataQualitySummary', async (config) => {
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const { system, user } = buildDataQualityPrompt(propertyId, quality)
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const raw = await chat(config, system, user)
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const json = extractJSON<unknown>(raw)
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const ai = json ? validateAIResponse(DataQualitySummaryResponseSchema, json, 'generateDataQualitySummary') : null
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if (!ai) {
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console.warn('[OpenRouterAIService] generateDataQualitySummary: invalid response — using mock fallback')
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const fb = await MockAIService.generateDataQualitySummary(propertyId, quality)
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return { ...fb, provenance: makeProvenance(config, 'mock', true, false) }
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}
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return {
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data: {
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overallAssessment: ai.overallAssessment,
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missingCriticalFields: ai.missingCriticalFields ?? quality.missingCriticalFields,
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recommendation: ai.recommendation,
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confidence: ai.confidence,
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},
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provenance: makeProvenance(config, 'ai', false, true),
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}
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}, () => MockAIService.generateDataQualitySummary(propertyId, quality))
|
||
},
|
||
|
||
// ── classifyMarketSignal ────────────────────────────────────────────────────
|
||
classifyMarketSignal(signalText: string): Promise<AIResponse<MarketSignalClassification>> {
|
||
return withFallback('classifyMarketSignal', async (config) => {
|
||
const { system, user } = buildMarketSignalPrompt(signalText)
|
||
const raw = await chat(config, system, user)
|
||
const json = extractJSON<unknown>(raw)
|
||
const ai = json
|
||
? validateAIResponse(MarketSignalClassificationResponseSchema, json, 'classifyMarketSignal')
|
||
: null
|
||
|
||
if (!ai) {
|
||
console.warn('[OpenRouterAIService] classifyMarketSignal: invalid response — using mock fallback')
|
||
const fb = await MockAIService.classifyMarketSignal(signalText)
|
||
return { ...fb, provenance: makeProvenance(config, 'mock', true, false) }
|
||
}
|
||
return {
|
||
data: {
|
||
signalType: ai.signalType,
|
||
probability: ai.probability,
|
||
timeHorizonMonths: ai.timeHorizonMonths ?? null,
|
||
areaSqmEstimate: ai.areaSqmEstimate ?? null,
|
||
credibility: ai.credibility,
|
||
reasoning: ai.reasoning,
|
||
},
|
||
provenance: makeProvenance(config, 'ai', false, true),
|
||
}
|
||
}, () => MockAIService.classifyMarketSignal(signalText))
|
||
},
|
||
|
||
// ── generateOfferEmail ──────────────────────────────────────────────────────
|
||
generateOfferEmail(payload: OfferEmailPayload): Promise<AIResponse<{ subject: string; body: string }>> {
|
||
return withFallback('generateOfferEmail', async (config) => {
|
||
const propertyList = payload.properties
|
||
.map((p, i) => `• ${p} (Match-Score: ${payload.matchScores[i]}%)`)
|
||
.join('\n')
|
||
const system = `Du bist Immobilienmakler bei Wincasa AG. Erstelle eine professionelle, knappe Angebotsmail auf Deutsch. Antworte als JSON: { "subject": "...", "body": "..." }`
|
||
const user = `Suchanfrage: "${payload.needTitle}"\n\nObjekte:\n${propertyList}\n\nErstelle eine professionelle Angebotsmail.`
|
||
const raw = await chat(config, system, user)
|
||
const json = extractJSON<unknown>(raw)
|
||
const ai = json ? validateAIResponse(OfferEmailResponseSchema, json, 'generateOfferEmail') : null
|
||
|
||
if (!ai) {
|
||
console.warn('[OpenRouterAIService] generateOfferEmail: invalid response — using mock fallback')
|
||
const fb = await MockAIService.generateOfferEmail(payload)
|
||
return { ...fb, provenance: makeProvenance(config, 'mock', true, false) }
|
||
}
|
||
return {
|
||
data: { subject: ai.subject, body: ai.body },
|
||
provenance: makeProvenance(config, 'ai', false, true),
|
||
}
|
||
}, () => MockAIService.generateOfferEmail(payload))
|
||
},
|
||
|
||
// ── Legacy: extractCriteria ─────────────────────────────────────────────────
|
||
extractCriteria(input: string): Promise<AIResponse<CriteriaExtractionResult>> {
|
||
return withFallback('extractCriteria', async (config) => {
|
||
const { system, user } = buildNeedParsingPrompt({ userInput: input })
|
||
const raw = await chat(config, system, user)
|
||
const json = extractJSON<RawNeedParseAI>(raw)
|
||
const ai = json ? validateAIResponse(NeedParsingResponseSchema, json, 'extractCriteria') : null
|
||
|
||
if (!ai) {
|
||
console.warn('[OpenRouterAIService] extractCriteria: invalid response — using mock fallback')
|
||
const fb = await MockAIService.extractCriteria(input)
|
||
return { ...fb, provenance: makeProvenance(config, 'mock', true, false) }
|
||
}
|
||
return {
|
||
data: {
|
||
extractedCriteria: {
|
||
assetType: ai.assetType as AssetType | undefined ?? undefined,
|
||
requiredArea: ai.areaRange ?? undefined,
|
||
preferredLocations: ai.preferredLocations ?? [],
|
||
budgetRange: ai.budgetRange ?? undefined,
|
||
},
|
||
confidence: 0.80,
|
||
missingFields: ai.missingFields ?? [],
|
||
assumptions: ai.assumptions ?? [],
|
||
followUpQuestions: (ai.missingFields ?? []).map(followUpForField),
|
||
},
|
||
provenance: makeProvenance(config, 'ai', false, true),
|
||
}
|
||
}, () => MockAIService.extractCriteria(input))
|
||
},
|
||
|
||
// ── Legacy: generateFollowUp ────────────────────────────────────────────────
|
||
generateFollowUp(partialNeed: Partial<CreateNeedInput>): Promise<AIResponse<string[]>> {
|
||
return withFallback('generateFollowUp', async (config) => {
|
||
const missingFields = [
|
||
...(!partialNeed.assetType ? ['assetType'] : []),
|
||
...(!partialNeed.preferredLocations?.length ? ['preferredLocations'] : []),
|
||
...(!partialNeed.timing ? ['timing'] : []),
|
||
...(!partialNeed.budgetRange ? ['budgetRange'] : []),
|
||
]
|
||
if (!missingFields.length) {
|
||
return { data: [], provenance: makeProvenance(config, 'ai', false, true) }
|
||
}
|
||
const { system, user } = buildFollowUpQuestionsPrompt({
|
||
criteria: partialNeed as ParsedNeedCriteria,
|
||
missingFields,
|
||
})
|
||
const raw = await chat(config, system, user)
|
||
const json = extractJSON<unknown[]>(raw)
|
||
const ai = json ? validateAIResponse(FollowUpQuestionsResponseSchema, json, 'generateFollowUp') : null
|
||
|
||
if (!ai?.length) {
|
||
console.warn('[OpenRouterAIService] generateFollowUp: invalid response — using mock fallback')
|
||
const fb = await MockAIService.generateFollowUp(partialNeed)
|
||
return { ...fb, provenance: makeProvenance(config, 'mock', true, false) }
|
||
}
|
||
return {
|
||
data: ai.map(q => q.questionText).filter(Boolean),
|
||
provenance: makeProvenance(config, 'ai', false, true),
|
||
}
|
||
}, () => MockAIService.generateFollowUp(partialNeed))
|
||
},
|
||
}
|