mirror of
https://github.com/samsonjs/spirit-tracker.git
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580 lines
19 KiB
JavaScript
580 lines
19 KiB
JavaScript
// viz/app/linker/suggestions.js
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import { tokenizeQuery, normSearchText } from "../sku.js";
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import {
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smwsKeyFromName,
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extractAgeFromText,
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filterSimTokens,
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tokenContainmentScore,
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fastSimilarityScore,
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similarityScore,
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} from "./similarity.js";
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/* ---------------- Randomization helpers ---------------- */
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function mulberry32(seed) {
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let t = seed >>> 0;
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return function () {
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t += 0x6d2b79f5;
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let x = Math.imul(t ^ (t >>> 15), 1 | t);
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x ^= x + Math.imul(x ^ (x >>> 7), 61 | x);
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return ((x ^ (x >>> 14)) >>> 0) / 4294967296;
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};
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}
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function shuffleInPlace(arr, rnd) {
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for (let i = arr.length - 1; i > 0; i--) {
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const j = (rnd() * (i + 1)) | 0;
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const tmp = arr[i];
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arr[i] = arr[j];
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arr[j] = tmp;
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}
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return arr;
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}
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/* ---------------- Suggestion helpers ---------------- */
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export function topSuggestions(allAgg, limit, otherPinnedSku, mappedSkus) {
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const scored = [];
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for (const it of allAgg) {
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if (!it) continue;
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if (mappedSkus && mappedSkus.has(String(it.sku))) continue;
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if (otherPinnedSku && String(it.sku) === String(otherPinnedSku)) continue;
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const stores = it.stores ? it.stores.size : 0;
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const hasPrice = it.cheapestPriceNum !== null ? 1 : 0;
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const hasName = it.name ? 1 : 0;
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const unknown = String(it.sku || "").startsWith("u:") ? 1 : 0;
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scored.push({ it, s: stores * 2 + hasPrice * 1.2 + hasName * 1.0 + unknown * 0.6 });
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}
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scored.sort((a, b) => b.s - a.s);
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return scored.slice(0, limit).map((x) => x.it);
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}
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// viz/app/linker/suggestions.js
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// (requires fnv1a32u(str) helper to exist in this file)
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export function recommendSimilar(
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allAgg,
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pinned,
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limit,
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otherPinnedSku,
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mappedSkus,
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isIgnoredPairFn,
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sizePenaltyFn,
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sameStoreFn,
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sameGroupFn
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) {
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if (!pinned || !pinned.name) return topSuggestions(allAgg, limit, otherPinnedSku, mappedSkus);
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const pinnedSku = String(pinned.sku || "");
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const otherSku = otherPinnedSku ? String(otherPinnedSku) : "";
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const base = String(pinned.name || "");
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const pinNorm = normSearchText(pinned.name || "");
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const pinRawToks = tokenizeQuery(pinNorm);
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const pinToks = filterSimTokens(pinRawToks);
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const pinBrand = pinToks[0] || "";
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const pinAge = extractAgeFromText(pinNorm);
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const pinnedSmws = smwsKeyFromName(pinned.name || "");
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// ---- Tuning knobs ----
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const MAX_SCAN = 5000; // cap for huge catalogs
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const FULL_SCAN_UNDER = 12000; // ✅ scan everything if catalog is "small"
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const MAX_CHEAP_KEEP = 320; // keep top candidates from cheap stage
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const MAX_FINE = 70; // expensive score only on top-N
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// ----------------------
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// Faster "topK" keeper: only sorts occasionally.
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function pushTopK(arr, item, k) {
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arr.push(item);
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if (arr.length >= k * 2) {
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arr.sort((a, b) => b.s - a.s);
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arr.length = k;
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}
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}
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const cheap = [];
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const nAll = allAgg.length || 0;
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if (!nAll) return [];
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// ✅ scan whole catalog when it's not huge
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const scanN = nAll <= FULL_SCAN_UNDER ? nAll : Math.min(MAX_SCAN, nAll);
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// ✅ rotate start to avoid alphabetical bias, but still cover scanN sequentially
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const start = (fnv1a32u(pinnedSku || pinNorm) % nAll) >>> 0;
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// Optional debug: uncomment to verify we’re actually hitting the region you expect
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// console.log("[linker] recommendSimilar scan2", { pinnedSku, nAll, scanN, start, startName: allAgg[start]?.name });
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for (let i = 0; i < scanN; i++) {
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const it = allAgg[(start + i) % nAll];
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if (!it) continue;
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const itSku = String(it.sku || "");
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if (!itSku) continue;
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if (itSku === pinnedSku) continue;
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if (otherSku && itSku === otherSku) continue;
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// HARD BLOCKS ONLY:
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if (typeof sameStoreFn === "function" && sameStoreFn(pinnedSku, itSku)) continue;
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if (typeof isIgnoredPairFn === "function" && isIgnoredPairFn(pinnedSku, itSku)) continue;
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if (typeof sameGroupFn === "function" && sameGroupFn(pinnedSku, itSku)) continue;
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// (Optional) original mapped exclusion lives here in your codebase.
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// Keep it if you want, but it wasn't your issue:
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if (mappedSkus && mappedSkus.has(itSku)) continue;
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// SMWS exact NUM.NUM match => keep at top
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if (pinnedSmws) {
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const k = smwsKeyFromName(it.name || "");
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if (k && k === pinnedSmws) {
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const stores = it.stores ? it.stores.size : 0;
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const hasPrice = it.cheapestPriceNum != null ? 1 : 0;
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pushTopK(
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cheap,
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{ it, s: 1e9 + stores * 10 + hasPrice, itNorm: "", itRawToks: null },
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MAX_CHEAP_KEEP
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);
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continue;
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}
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}
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const itNorm = normSearchText(it.name || "");
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if (!itNorm) continue;
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const itRawToks = tokenizeQuery(itNorm);
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const itToks = filterSimTokens(itRawToks);
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if (!itToks.length) continue;
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const itBrand = itToks[0] || "";
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const firstMatch = pinBrand && itBrand && pinBrand === itBrand;
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const contain = tokenContainmentScore(pinRawToks, itRawToks);
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// Cheap score first (no Levenshtein)
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let s0 = fastSimilarityScore(pinRawToks, itRawToks, pinNorm, itNorm);
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if (s0 <= 0) s0 = 0.01 + 0.25 * contain;
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// Soft first-token mismatch penalty (never blocks)
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if (!firstMatch) {
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const smallN = Math.min(pinToks.length || 0, itToks.length || 0);
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let mult = 0.10 + 0.95 * contain;
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if (smallN <= 3 && contain < 0.78) mult *= 0.22;
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s0 *= Math.min(1.0, mult);
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}
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// Size penalty early
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if (typeof sizePenaltyFn === "function") {
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s0 *= sizePenaltyFn(pinnedSku, itSku);
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}
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// Age handling early
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const itAge = extractAgeFromText(itNorm);
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if (pinAge && itAge) {
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if (pinAge === itAge) s0 *= 1.6;
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else s0 *= 0.22;
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}
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// Unknown boost
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if (pinnedSku.startsWith("u:") || itSku.startsWith("u:")) s0 *= 1.08;
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pushTopK(cheap, { it, s: s0, itNorm, itRawToks }, MAX_CHEAP_KEEP);
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}
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// Final trim/sort for cheap stage
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cheap.sort((a, b) => b.s - a.s);
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if (cheap.length > MAX_CHEAP_KEEP) cheap.length = MAX_CHEAP_KEEP;
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// Fine stage: expensive scoring only on top candidates
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const fine = [];
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for (const x of cheap.slice(0, MAX_FINE)) {
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const it = x.it;
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const itSku = String(it.sku || "");
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let s = similarityScore(base, it.name || "");
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if (s <= 0) continue;
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const itNorm = x.itNorm || normSearchText(it.name || "");
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const itRawToks = x.itRawToks || tokenizeQuery(itNorm);
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const itToks = filterSimTokens(itRawToks);
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const itBrand = itToks[0] || "";
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const firstMatch = pinBrand && itBrand && pinBrand === itBrand;
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const contain = tokenContainmentScore(pinRawToks, itRawToks);
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if (!firstMatch) {
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const smallN = Math.min(pinToks.length || 0, itToks.length || 0);
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let mult = 0.10 + 0.95 * contain;
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if (smallN <= 3 && contain < 0.78) mult *= 0.22;
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s *= Math.min(1.0, mult);
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if (s <= 0) continue;
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}
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if (typeof sizePenaltyFn === "function") {
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s *= sizePenaltyFn(pinnedSku, itSku);
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if (s <= 0) continue;
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}
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const itAge = extractAgeFromText(itNorm);
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if (pinAge && itAge) {
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if (pinAge === itAge) s *= 2.0;
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else s *= 0.15;
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}
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if (pinnedSku.startsWith("u:") || itSku.startsWith("u:")) s *= 1.12;
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fine.push({ it, s });
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}
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fine.sort((a, b) => b.s - a.s);
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const out = fine.slice(0, limit).map((x) => x.it);
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if (out.length) return out;
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// Fallback (unchanged)
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const fallback = [];
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for (const it of allAgg) {
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if (!it) continue;
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const itSku = String(it.sku || "");
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if (!itSku) continue;
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if (itSku === pinnedSku) continue;
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if (otherSku && itSku === otherSku) continue;
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if (typeof sameStoreFn === "function" && sameStoreFn(pinnedSku, itSku)) continue;
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if (typeof isIgnoredPairFn === "function" && isIgnoredPairFn(pinnedSku, itSku)) continue;
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if (typeof sameGroupFn === "function" && sameGroupFn(pinnedSku, itSku)) continue;
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const stores = it.stores ? it.stores.size : 0;
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const hasPrice = it.cheapestPriceNum !== null ? 1 : 0;
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const hasName = it.name ? 1 : 0;
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fallback.push({ it, s: stores * 2 + hasPrice * 1.2 + hasName * 1.0 });
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if (fallback.length >= 250) break;
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}
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fallback.sort((a, b) => b.s - a.s);
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return fallback.slice(0, limit).map((x) => x.it);
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}
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export function computeInitialPairsFast(
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allAgg,
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mappedSkus,
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limitPairs,
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isIgnoredPairFn,
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sameStoreFn,
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sizePenaltyFn // ✅ NEW: pass sizePenaltyForPair in
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) {
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const itemsAll = allAgg.filter((it) => !!it);
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const seed = (Date.now() ^ ((Math.random() * 1e9) | 0)) >>> 0;
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const rnd = mulberry32(seed);
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const itemsShuf = itemsAll.slice();
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shuffleInPlace(itemsShuf, rnd);
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// Bigger cap is fine; still bounded
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const WORK_CAP = Math.min(9000, itemsShuf.length);
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const workAll = itemsShuf.length > WORK_CAP ? itemsShuf.slice(0, WORK_CAP) : itemsShuf;
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// Unmapped-only view for normal similarity stage
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const work = workAll.filter((it) => {
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if (!it) return false;
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return !(mappedSkus && mappedSkus.has(String(it.sku)));
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});
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function itemRank(it) {
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const stores = it.stores ? it.stores.size : 0;
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const hasPrice = it.cheapestPriceNum != null ? 1 : 0;
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const hasName = it.name ? 1 : 0;
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const unknown = String(it.sku || "").startsWith("u:") ? 1 : 0;
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return stores * 3 + hasPrice * 2 + hasName * 0.5 + unknown * 0.25;
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}
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// --- SMWS exact-code pairs first (kept as-is, but apply sameStore/isIgnored) ---
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function smwsPairsFirst(workArr, limit) {
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const buckets = new Map(); // code -> items[]
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for (const it of workArr) {
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if (!it) continue;
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const sku = String(it.sku || "");
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if (!sku) continue;
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const code = smwsKeyFromName(it.name || "");
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if (!code) continue;
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let arr = buckets.get(code);
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if (!arr) buckets.set(code, (arr = []));
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arr.push(it);
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}
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const candPairs = [];
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for (const arr0 of buckets.values()) {
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if (!arr0 || arr0.length < 2) continue;
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const arr = arr0
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.slice()
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.sort((a, b) => itemRank(b) - itemRank(a))
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.slice(0, 80);
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// Prefer an unmapped anchor if possible; otherwise best overall
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const anchor = arr.slice().sort((a, b) => itemRank(b) - itemRank(a))[0];
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if (!anchor) continue;
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for (const u of arr) {
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if (u === anchor) continue;
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const a = anchor;
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const b = u;
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const aSku = String(a.sku || "");
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const bSku = String(b.sku || "");
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if (!aSku || !bSku || aSku === bSku) continue;
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// Only link *unmapped* targets in this stage
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if (mappedSkus && mappedSkus.has(bSku)) continue;
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if (typeof sameStoreFn === "function" && sameStoreFn(aSku, bSku)) continue;
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if (typeof isIgnoredPairFn === "function" && isIgnoredPairFn(aSku, bSku)) continue;
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const s = 1e9 + itemRank(a) + itemRank(b);
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candPairs.push({ a, b, score: s });
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}
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}
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candPairs.sort((x, y) => y.score - x.score);
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const usedUnmapped = new Set();
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const out0 = [];
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for (const p of candPairs) {
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const bSku = String(p.b.sku || "");
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if (!bSku) continue;
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if (usedUnmapped.has(bSku)) continue;
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usedUnmapped.add(bSku);
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out0.push(p);
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if (out0.length >= limit) break;
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}
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return { pairs: out0, usedUnmapped };
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}
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const smwsFirst = smwsPairsFirst(workAll, limitPairs);
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const used = new Set(smwsFirst.usedUnmapped);
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const out = smwsFirst.pairs.slice();
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if (out.length >= limitPairs) return out.slice(0, limitPairs);
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// --- Improved general pairing logic (uses same “good” scoring knobs) ---
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const seeds = topSuggestions(work, Math.min(220, work.length), "", mappedSkus).filter(
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(it) => !used.has(String(it?.sku || ""))
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);
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// Build token buckets over *normalized* names (better hits)
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const TOKEN_BUCKET_CAP = 700;
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const tokMap = new Map(); // token -> items[]
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const itemRawToks = new Map(); // sku -> raw tokens
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const itemNorm = new Map(); // sku -> norm name
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const itemFilt = new Map(); // sku -> filtered tokens (for first-token logic)
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for (const it of work) {
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const sku = String(it.sku || "");
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if (!sku) continue;
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const n = normSearchText(it.name || "");
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const raw = tokenizeQuery(n);
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const filt = filterSimTokens(raw);
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itemNorm.set(sku, n);
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itemRawToks.set(sku, raw);
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itemFilt.set(sku, filt);
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// bucket using a handful of filtered tokens (higher signal)
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for (const t of filt.slice(0, 12)) {
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let arr = tokMap.get(t);
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if (!arr) tokMap.set(t, (arr = []));
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if (arr.length < TOKEN_BUCKET_CAP) arr.push(it);
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}
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}
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const bestByPair = new Map();
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const MAX_CAND_TOTAL = 450;
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const MAX_CHEAP = 40;
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const MAX_FINE = 18;
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for (const a of seeds) {
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const aSku = String(a.sku || "");
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if (!aSku || used.has(aSku)) continue;
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const aNorm = itemNorm.get(aSku) || normSearchText(a.name || "");
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const aRaw = itemRawToks.get(aSku) || tokenizeQuery(aNorm);
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const aFilt = itemFilt.get(aSku) || filterSimTokens(aRaw);
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if (!aFilt.length) continue;
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const aBrand = aFilt[0] || "";
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const aAge = extractAgeFromText(aNorm);
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// Gather candidates from token buckets
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const cand = new Map();
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for (const t of aFilt.slice(0, 10)) {
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const arr = tokMap.get(t);
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if (!arr) continue;
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for (let i = 0; i < arr.length && cand.size < MAX_CAND_TOTAL; i++) {
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const b = arr[i];
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if (!b) continue;
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const bSku = String(b.sku || "");
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if (!bSku || bSku === aSku) continue;
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if (used.has(bSku)) continue;
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if (mappedSkus && mappedSkus.has(bSku)) continue;
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if (typeof isIgnoredPairFn === "function" && isIgnoredPairFn(aSku, bSku)) continue;
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if (typeof sameStoreFn === "function" && sameStoreFn(aSku, bSku)) continue;
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cand.set(bSku, b);
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}
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if (cand.size >= MAX_CAND_TOTAL) break;
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}
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if (!cand.size) continue;
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// Cheap score stage (fastSimilarity + containment + size + age + first-token mismatch penalty)
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const cheap = [];
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for (const b of cand.values()) {
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const bSku = String(b.sku || "");
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const bNorm = itemNorm.get(bSku) || normSearchText(b.name || "");
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const bRaw = itemRawToks.get(bSku) || tokenizeQuery(bNorm);
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const bFilt = itemFilt.get(bSku) || filterSimTokens(bRaw);
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if (!bFilt.length) continue;
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const contain = tokenContainmentScore(aRaw, bRaw);
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const bBrand = bFilt[0] || "";
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const firstMatch = aBrand && bBrand && aBrand === bBrand;
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let s = fastSimilarityScore(aRaw, bRaw, aNorm, bNorm);
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if (s <= 0) s = 0.01 + 0.25 * contain;
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if (!firstMatch) {
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const smallN = Math.min(aFilt.length || 0, bFilt.length || 0);
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let mult = 0.10 + 0.95 * contain;
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if (smallN <= 3 && contain < 0.78) mult *= 0.22;
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s *= Math.min(1.0, mult);
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}
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if (typeof sizePenaltyFn === "function") s *= sizePenaltyFn(aSku, bSku);
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const bAge = extractAgeFromText(bNorm);
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if (aAge && bAge) {
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if (aAge === bAge) s *= 1.6;
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else s *= 0.22;
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}
|
||
|
||
if (String(aSku).startsWith("u:") || String(bSku).startsWith("u:")) s *= 1.06;
|
||
|
||
if (s > 0) cheap.push({ b, s, bNorm, bRaw, bFilt, contain, firstMatch, bAge });
|
||
}
|
||
|
||
if (!cheap.length) continue;
|
||
cheap.sort((x, y) => y.s - x.s);
|
||
|
||
// Fine stage (expensive similarityScore + same penalties again)
|
||
let bestB = null;
|
||
let bestS = 0;
|
||
|
||
for (const x of cheap.slice(0, MAX_FINE)) {
|
||
const b = x.b;
|
||
const bSku = String(b.sku || "");
|
||
|
||
let s = similarityScore(a.name || "", b.name || "");
|
||
if (s <= 0) continue;
|
||
|
||
// first-token mismatch soft penalty
|
||
if (!x.firstMatch) {
|
||
const smallN = Math.min(aFilt.length || 0, (x.bFilt || []).length || 0);
|
||
let mult = 0.10 + 0.95 * x.contain;
|
||
if (smallN <= 3 && x.contain < 0.78) mult *= 0.22;
|
||
s *= Math.min(1.0, mult);
|
||
if (s <= 0) continue;
|
||
}
|
||
|
||
if (typeof sizePenaltyFn === "function") {
|
||
s *= sizePenaltyFn(aSku, bSku);
|
||
if (s <= 0) continue;
|
||
}
|
||
|
||
if (aAge && x.bAge) {
|
||
if (aAge === x.bAge) s *= 2.0;
|
||
else s *= 0.15;
|
||
}
|
||
|
||
if (String(aSku).startsWith("u:") || String(bSku).startsWith("u:")) s *= 1.10;
|
||
|
||
if (s > bestS) {
|
||
bestS = s;
|
||
bestB = b;
|
||
}
|
||
}
|
||
|
||
// Threshold (slightly lower than before, because we now punish mismatches more intelligently)
|
||
if (!bestB || bestS < 0.50) continue;
|
||
|
||
const bSku = String(bestB.sku || "");
|
||
if (!bSku || used.has(bSku)) continue;
|
||
|
||
const key = aSku < bSku ? `${aSku}|${bSku}` : `${bSku}|${aSku}`;
|
||
const prev = bestByPair.get(key);
|
||
if (!prev || bestS > prev.score) bestByPair.set(key, { a, b: bestB, score: bestS });
|
||
}
|
||
|
||
const pairs = Array.from(bestByPair.values());
|
||
pairs.sort((x, y) => y.score - x.score);
|
||
|
||
// ---- light randomness inside a top band (same behavior as before) ----
|
||
const need = Math.max(0, limitPairs - out.length);
|
||
if (!need) return out.slice(0, limitPairs);
|
||
|
||
const TOP_BAND = Math.min(700, pairs.length);
|
||
const JITTER = 0.08;
|
||
|
||
const band = pairs.slice(0, TOP_BAND).map((p) => {
|
||
const jitter = (rnd() - 0.5) * JITTER;
|
||
return { ...p, _rank: p.score * (1 + jitter) };
|
||
});
|
||
band.sort((a, b) => b._rank - a._rank);
|
||
|
||
function tryTake(p) {
|
||
const aSku = String(p.a.sku || "");
|
||
const bSku = String(p.b.sku || "");
|
||
if (!aSku || !bSku || aSku === bSku) return false;
|
||
if (used.has(aSku) || used.has(bSku)) return false;
|
||
if (typeof sameStoreFn === "function" && sameStoreFn(aSku, bSku)) return false;
|
||
if (typeof isIgnoredPairFn === "function" && isIgnoredPairFn(aSku, bSku)) return false;
|
||
|
||
used.add(aSku);
|
||
used.add(bSku);
|
||
out.push({ a: p.a, b: p.b, score: p.score });
|
||
return true;
|
||
}
|
||
|
||
for (const p of band) {
|
||
if (out.length >= limitPairs) break;
|
||
tryTake(p);
|
||
}
|
||
|
||
if (out.length < limitPairs) {
|
||
for (let i = TOP_BAND; i < pairs.length; i++) {
|
||
if (out.length >= limitPairs) break;
|
||
tryTake(pairs[i]);
|
||
}
|
||
}
|
||
|
||
return out.slice(0, limitPairs);
|
||
}
|
||
|
||
|
||
|
||
|
||
|
||
function fnv1a32u(str) {
|
||
let h = 0x811c9dc5;
|
||
str = String(str || "");
|
||
for (let i = 0; i < str.length; i++) {
|
||
h ^= str.charCodeAt(i);
|
||
h = Math.imul(h, 0x01000193);
|
||
}
|
||
return h >>> 0;
|
||
}
|
||
|