 Vasyka
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1ff888131f
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Stage 16 — AI Layer: VIN decoder + diagnostic / parts / price helpers
VinDecoder (deterministic, no API):
- ISO 3779/3780 parsing: WMI manufacturer (~60 brands), year (cyclical with
post-2010 disambiguation via position 7), region, plant, NA checksum
- Strip non-VIN chars, accept dashes/spaces, reject I/O/Q per spec
AiAssistantService:
- Refactored provider HTTP into postClaude/postOpenAI/postGemini so both
chat history and one-shot calls share the same transport
- singleShot(system, userPrompt, provider?) for fire-and-forget calls
- 4 specialized helpers with tight prompts:
- suggestDiagnosis(WO) — diagnostician based on complaint + VIN info
- suggestParts(WO, task) — OEM parts list for an operation
- suggestPrice(Part) — markup recommendation with justification
- vinRecommendations(vin, mileage) — scheduled maintenance from decoded VIN
- monthlyUsage() — token spend MTD by provider
Filament:
- VehicleResource: "Decode VIN" + "AI: recomandări" actions
- WorkOrderResource Edit: "AI: sugerează diagnostic" header action
- PartResource: "AI: preț recomandat" action
- Shared views: filament.tenant.ai-reply, filament.tenant.vin-decode
- AiAssistant page shows monthly token usage banner
Tests (13 new):
- 8 VinDecoder unit tests with real VIN samples (Honda 2003, VW 1999, Audi
2014, Dacia, unknown WMI, lowercase/dashes, forbidden chars)
- 5 AiHelpers feature tests with Http::fake covering all providers + no-key
fallback + token usage aggregation
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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2026-05-27 20:24:09 +00:00 |
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