feat: add UPC to ASIN mapping and large file UPC analysis
Introduces the capability to resolve UPCs to ASINs using the Keepa API. This includes a new `upc-file` command for processing large Excel files of UPCs, a `upc` CLI tool for quick lookups, and API endpoints for web-based integration. The analysis pipeline was refactored into a reusable module to support both standard ASIN leads and new UPC-driven workflows.
This commit is contained in:
Victor Noguera
219
src/index.ts
219
src/index.ts
@@ -1,22 +1,12 @@
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import { readProducts } from "./reader.ts";
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import { fetchKeepaDataBatch } from "./keepa.ts";
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import { fetchSellabilityBatch, fetchSpApiPricingAndFees } from "./sp-api.ts";
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import { connectCache, getCache, setCache, disconnectCache } from "./cache.ts";
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import { analyzeProducts } from "./llm.ts";
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import { connectCache, disconnectCache } from "./cache.ts";
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import { printResults, writeResultsToDb } from "./writer.ts";
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import { initDb, closeDb } from "./database.ts";
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import { chunkArray, processProductChunk } from "./analysis-pipeline.ts";
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import path from "node:path";
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import type {
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EnrichedProduct,
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AnalysisResult,
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KeepaData,
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ProductRecord,
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SellabilityInfo,
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SpApiData,
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} from "./types.ts";
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import type { AnalysisResult } from "./types.ts";
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const DB_PATH = "./results.db";
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const LLM_BATCH_SIZE = 5;
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const INPUT_BATCH_SIZE = 50;
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function parseArgs(): { inputFile: string; outputFile?: string } {
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@@ -35,14 +25,6 @@ function parseArgs(): { inputFile: string; outputFile?: string } {
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return { inputFile, outputFile };
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}
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function chunkArray<T>(items: T[], chunkSize: number): T[][] {
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const chunks: T[][] = [];
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for (let i = 0; i < items.length; i += chunkSize) {
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chunks.push(items.slice(i, i + chunkSize));
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}
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return chunks;
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}
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function resolveBaseOutputPath(inputFile: string, outputFile?: string): string {
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if (outputFile) return outputFile;
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@@ -50,201 +32,6 @@ function resolveBaseOutputPath(inputFile: string, outputFile?: string): string {
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return path.join(parsedInput.dir, `${parsedInput.name}_results.xlsx`);
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}
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async function processProductChunk(
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products: ProductRecord[],
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): Promise<AnalysisResult[]> {
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console.log(`\nChecking cache for ${products.length} products...`);
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const cached = new Map<string, EnrichedProduct>();
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const excludedCachedAsins = new Set<string>();
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const uncachedProducts: ProductRecord[] = [];
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for (const p of products) {
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const hit = await getCache(p.asin);
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if (hit) {
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if (hit.spApi.sellabilityStatus === "available") {
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console.log(` [cache hit] ${p.asin}`);
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cached.set(p.asin, hit);
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} else {
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excludedCachedAsins.add(p.asin);
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console.log(
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` [exclude cached] ${p.asin} — status=${hit.spApi.sellabilityStatus}`,
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);
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}
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} else {
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uncachedProducts.push(p);
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}
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}
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console.log(
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`${cached.size} cached available, ${excludedCachedAsins.size} cached excluded, ${uncachedProducts.length} to fetch`,
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);
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const sellabilityMap = new Map<string, SellabilityInfo>();
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const availableProducts: ProductRecord[] = [];
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const unavailableProducts: ProductRecord[] = [];
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if (uncachedProducts.length > 0) {
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console.log(
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`\nChecking sellability for ${uncachedProducts.length} ASINs...`,
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);
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const sellResults = await fetchSellabilityBatch(
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uncachedProducts.map((p) => p.asin),
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);
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for (const p of uncachedProducts) {
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const info = sellResults.get(p.asin) ?? {
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canSell: null,
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sellabilityStatus: "unknown" as const,
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sellabilityReason: "Sellability check returned no result",
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};
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sellabilityMap.set(p.asin, info);
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if (info.sellabilityStatus === "available") {
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availableProducts.push(p);
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console.log(` [available] ${p.asin} — status=${info.sellabilityStatus}`);
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} else {
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unavailableProducts.push(p);
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console.log(
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` [exclude] ${p.asin} — status=${info.sellabilityStatus}, reason=${info.sellabilityReason ?? "n/a"}`,
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);
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}
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}
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console.log(
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`\nSellability gate: ${availableProducts.length} available, ${unavailableProducts.length} excluded`,
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);
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}
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let keepaResults = new Map<string, KeepaData>();
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if (availableProducts.length > 0) {
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console.log(`\nFetching ${availableProducts.length} ASINs from Keepa...`);
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try {
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keepaResults = await fetchKeepaDataBatch(
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availableProducts.map((p) => p.asin),
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);
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} catch (err) {
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console.warn(`Keepa batch fetch failed: ${err}`);
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}
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}
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console.log(
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`\nFetching pricing & fees for ${availableProducts.length} ASINs...`,
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);
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const spApiResults = new Map<string, SpApiData>();
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const pricingQueue = [...availableProducts];
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let pricingDone = 0;
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async function fetchNextPricing(): Promise<void> {
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while (pricingQueue.length > 0) {
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const p = pricingQueue.shift()!;
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const sellability = sellabilityMap.get(p.asin)!;
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const spApi = await fetchSpApiPricingAndFees(p.asin, sellability);
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const keepa = keepaResults.get(p.asin);
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if (keepa?.currentPrice && spApi.estimatedSalePrice === 0) {
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spApi.estimatedSalePrice = keepa.currentPrice;
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}
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spApiResults.set(p.asin, spApi);
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pricingDone++;
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if (pricingDone % 10 === 0 || pricingDone === availableProducts.length) {
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console.log(
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` [pricing] ${pricingDone}/${availableProducts.length} fetched`,
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);
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}
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}
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}
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const pricingWorkers = Array.from(
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{ length: Math.min(5, availableProducts.length || 1) },
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() => fetchNextPricing(),
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);
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await Promise.all(pricingWorkers);
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console.log(`\nEnriching products...`);
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const enriched: EnrichedProduct[] = [];
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const availableAsins = new Set(availableProducts.map((ap) => ap.asin));
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for (const p of products) {
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if (excludedCachedAsins.has(p.asin)) {
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continue;
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}
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const cachedProduct = cached.get(p.asin);
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if (cachedProduct) {
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enriched.push(cachedProduct);
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continue;
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}
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if (!availableAsins.has(p.asin)) {
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continue;
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}
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const keepa = keepaResults.get(p.asin) ?? null;
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const spApi = spApiResults.get(p.asin) ?? {
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fbaFee: 5.0,
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fbmFee: 1.5,
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referralFeePercent: 15,
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estimatedSalePrice: 0,
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canSell: null,
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sellabilityStatus: "unknown" as const,
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sellabilityReason: "SP-API data missing",
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};
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const product: EnrichedProduct = {
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record: p,
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keepa,
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spApi,
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fetchedAt: new Date().toISOString(),
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};
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await setCache(p.asin, product);
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enriched.push(product);
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}
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console.log(
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`\nAnalyzing ${enriched.length} products via LLM (batch size: ${LLM_BATCH_SIZE})...\n`,
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);
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const results: AnalysisResult[] = [];
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for (let i = 0; i < enriched.length; i += LLM_BATCH_SIZE) {
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const batch = enriched.slice(i, i + LLM_BATCH_SIZE);
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const batchNum = Math.floor(i / LLM_BATCH_SIZE) + 1;
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const totalBatches = Math.ceil(enriched.length / LLM_BATCH_SIZE);
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console.log(` LLM batch ${batchNum}/${totalBatches}...`);
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if (i > 0) {
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await new Promise((r) => setTimeout(r, 5000));
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}
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let verdicts;
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try {
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verdicts = await analyzeProducts(batch);
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} catch {
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await new Promise((r) => setTimeout(r, 10_000));
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try {
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verdicts = await analyzeProducts(batch);
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} catch {
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verdicts = null;
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}
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}
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for (let j = 0; j < batch.length; j++) {
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results.push({
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product: batch[j]!,
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verdict: verdicts?.[j] ?? {
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asin: batch[j]!.record.asin,
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verdict: "SKIP",
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confidence: 0,
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reasoning: "LLM analysis failed",
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},
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});
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}
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}
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return results;
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}
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async function main() {
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const { inputFile, outputFile } = parseArgs();
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