feat: AI grading v3 — 8 subgrades, card detection, ML dataset#109
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… dataset pipeline - 8 subgrades (centering/corners/edges/surface x front/back) with 60/40 weighting - Card boundary detection via Haiku preflight — auto-crops user photos with background - Passive slab image collection from eBay sold listings into grading-dataset Firestore - Token usage + cost tracking per grade - Overall formula: (front*0.60 + back*0.40), capped at lowest subgrade + 1 - 172 unit tests, ~130 API tests
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| const imgRes = await axios.get(imageUrl, { | ||
| responseType: "arraybuffer", | ||
| timeout: 15_000, | ||
| maxRedirects: 5, | ||
| }); |
DNS-resolves hostnames and blocks private IPs, cloud metadata endpoints, and non-HTTP(S) schemes in detectAndCropCard and cropCorners.
…ction - Changelog v1.3.0: 8-subgrade grading, card detection, ML dataset, SSRF protection - README: version bump, updated AI grading description - Internals: v3 pipeline, SSRF validation, new Firestore collections, test counts - Preprocessing: SSRF-safe image fetch with DNS resolution + private IP blocking
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Summary
grading-datasetFirestore collection. Owner-only stats endpoint.Test plan
node test/unit-test.js— 172 tests pass (roundGrade, image blocks, v3 formula, price trend edges)/api/grading-dataset/stats,/api/autocomplete,/api/sets/:setCode/api/gradewith front + back images — verify 8 subgrades +mode: "llm-detailed-v3"/api/gradewith front only — verify fallback with limitation notecardDetectionfield populated when user photo has background