Refactor SP-API test script and improve type definitions
- Updated `sp-test.ts` to enhance argument parsing and error handling for sellability checks. - Refactored `types.ts` to maintain consistent formatting and improve readability. - Improved `writer.ts` for better result handling and CSV writing, ensuring clarity in output. - Adjusted `tsconfig.json` formatting for consistency and readability.
This commit is contained in:
Victor Noguera
1068
src/bestsellers-by-category.ts
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1068
src/bestsellers-by-category.ts
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File diff suppressed because it is too large
Load Diff
132
src/cache.ts
132
src/cache.ts
@@ -1,66 +1,66 @@
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import Redis from "ioredis";
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import { config } from "./config.ts";
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import type { EnrichedProduct } from "./types.ts";
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let redis: Redis | null = null;
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let disabled = false;
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export async function connectCache(): Promise<void> {
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if (disabled) return;
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try {
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redis = new Redis(config.redisUrl, {
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maxRetriesPerRequest: 1,
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connectTimeout: 3000,
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lazyConnect: true,
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retryStrategy: () => null,
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reconnectOnError: () => false,
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});
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// Swallow connection-level errors after we intentionally disable cache.
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redis.on("error", () => {
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// no-op
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});
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await redis.connect();
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console.log("Redis connected");
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} catch (err) {
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console.warn(`Redis unavailable, running without cache: ${err}`);
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if (redis) {
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redis.disconnect();
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}
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redis = null;
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disabled = true;
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}
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}
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export async function getCache(asin: string): Promise<EnrichedProduct | null> {
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if (!redis) return null;
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try {
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const data = await redis.get(`asin:${asin}`);
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return data ? JSON.parse(data) : null;
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} catch {
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return null;
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}
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}
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export async function setCache(
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asin: string,
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data: EnrichedProduct,
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): Promise<void> {
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if (!redis) return;
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try {
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await redis.set(
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`asin:${asin}`,
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JSON.stringify(data),
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"EX",
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config.cacheTtl,
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);
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} catch {
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// Non-critical, continue without caching
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}
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}
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export async function disconnectCache(): Promise<void> {
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if (redis) {
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await redis.quit();
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redis = null;
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}
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}
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import Redis from "ioredis";
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import { config } from "./config.ts";
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import type { EnrichedProduct } from "./types.ts";
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let redis: Redis | null = null;
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let disabled = false;
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export async function connectCache(): Promise<void> {
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if (disabled) return;
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try {
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redis = new Redis(config.redisUrl, {
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maxRetriesPerRequest: 1,
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connectTimeout: 3000,
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lazyConnect: true,
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retryStrategy: () => null,
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reconnectOnError: () => false,
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});
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// Swallow connection-level errors after we intentionally disable cache.
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redis.on("error", () => {
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// no-op
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});
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await redis.connect();
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console.log("Redis connected");
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} catch (err) {
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console.warn(`Redis unavailable, running without cache: ${err}`);
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if (redis) {
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redis.disconnect();
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}
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redis = null;
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disabled = true;
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}
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}
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export async function getCache(asin: string): Promise<EnrichedProduct | null> {
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if (!redis) return null;
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try {
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const data = await redis.get(`asin:${asin}`);
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return data ? JSON.parse(data) : null;
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} catch {
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return null;
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}
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}
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export async function setCache(
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asin: string,
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data: EnrichedProduct,
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): Promise<void> {
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if (!redis) return;
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try {
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await redis.set(
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`asin:${asin}`,
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JSON.stringify(data),
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"EX",
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config.cacheTtl,
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);
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} catch {
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// Non-critical, continue without caching
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}
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}
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export async function disconnectCache(): Promise<void> {
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if (redis) {
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await redis.quit();
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redis = null;
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}
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}
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@@ -1,34 +1,34 @@
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function required(key: string): string {
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const val = Bun.env[key];
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if (!val) throw new Error(`Missing required env var: ${key}`);
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return val;
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}
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function optional(key: string, fallback: string): string {
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return Bun.env[key] || fallback;
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}
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function optionalBoolean(key: string, fallback: boolean): boolean {
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const raw = Bun.env[key];
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if (!raw) return fallback;
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const value = raw.trim().toLowerCase();
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return value === "1" || value === "true" || value === "yes";
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}
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export const config = {
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keepaApiKey: required("KEEPA_API_KEY"),
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redisUrl: optional("REDIS_URL", "redis://localhost:6379"),
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llmUrl: optional("LLM_URL", "http://localhost:1234/v1"),
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llmModel: optional("LLM_MODEL", "default"),
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cacheTtl: parseInt(optional("CACHE_TTL", "86400"), 10),
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spApiClientId: Bun.env.SP_API_CLIENT_ID,
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spApiClientSecret: Bun.env.SP_API_CLIENT_SECRET,
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spApiRefreshToken: Bun.env.SP_API_REFRESH_TOKEN,
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spApiRegion: optional("SP_API_REGION", "na"),
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spApiMarketplaceId: optional("SP_API_MARKETPLACE_ID", "ATVPDKIKX0DER"),
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spApiSellerId: Bun.env.SP_API_SELLER_ID,
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spApiUseSandbox: optionalBoolean("SP_API_USE_SANDBOX", false),
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awsAccessKeyId: Bun.env.AWS_ACCESS_KEY_ID,
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awsSecretAccessKey: Bun.env.AWS_SECRET_ACCESS_KEY,
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awsSessionToken: Bun.env.AWS_SESSION_TOKEN,
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} as const;
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function required(key: string): string {
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const val = Bun.env[key];
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if (!val) throw new Error(`Missing required env var: ${key}`);
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return val;
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}
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function optional(key: string, fallback: string): string {
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return Bun.env[key] || fallback;
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}
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function optionalBoolean(key: string, fallback: boolean): boolean {
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const raw = Bun.env[key];
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if (!raw) return fallback;
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const value = raw.trim().toLowerCase();
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return value === "1" || value === "true" || value === "yes";
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}
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export const config = {
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keepaApiKey: required("KEEPA_API_KEY"),
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redisUrl: optional("REDIS_URL", "redis://localhost:6379"),
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llmUrl: optional("LLM_URL", "http://localhost:1234/v1"),
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llmModel: optional("LLM_MODEL", "default"),
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cacheTtl: parseInt(optional("CACHE_TTL", "86400"), 10),
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spApiClientId: Bun.env.SP_API_CLIENT_ID,
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spApiClientSecret: Bun.env.SP_API_CLIENT_SECRET,
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spApiRefreshToken: Bun.env.SP_API_REFRESH_TOKEN,
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spApiRegion: optional("SP_API_REGION", "na"),
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spApiMarketplaceId: optional("SP_API_MARKETPLACE_ID", "ATVPDKIKX0DER"),
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spApiSellerId: Bun.env.SP_API_SELLER_ID,
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spApiUseSandbox: optionalBoolean("SP_API_USE_SANDBOX", false),
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awsAccessKeyId: Bun.env.AWS_ACCESS_KEY_ID,
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awsSecretAccessKey: Bun.env.AWS_SECRET_ACCESS_KEY,
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awsSessionToken: Bun.env.AWS_SESSION_TOKEN,
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} as const;
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690
src/index.ts
690
src/index.ts
@@ -1,345 +1,345 @@
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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 { printResults, writeResultsCsv } from "./writer.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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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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const args = process.argv.slice(2);
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const inputFile = args.find((a) => !a.startsWith("--"));
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const outIdx = args.indexOf("--out");
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const outputFile = outIdx !== -1 ? args[outIdx + 1] : undefined;
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if (!inputFile) {
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console.error(
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"Usage: bun run src/index.ts <input.csv|xlsx> [--out results.csv]",
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);
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process.exit(1);
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}
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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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const parsedInput = path.parse(inputFile);
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return path.join(parsedInput.dir, `${parsedInput.name}_results.xlsx`);
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}
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function buildChunkOutputPath(
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baseOutputPath: string,
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chunkIndex: number,
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): string {
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const parsed = path.parse(baseOutputPath);
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const extension = parsed.ext || ".xlsx";
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const chunkSuffix = String(chunkIndex + 1).padStart(3, "0");
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return path.join(
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parsed.dir,
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`${parsed.name}_part_${chunkSuffix}${extension}`,
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);
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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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// Phase 2: Check cache for all ASINs in chunk
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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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// Phase 3: Sellability gate — check uncached ASINs before anything else
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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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// Keep only ASINs that are explicitly available.
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if (info.sellabilityStatus === "available") {
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availableProducts.push(p);
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console.log(
|
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` [available] ${p.asin} — status=${info.sellabilityStatus}`,
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);
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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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|
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// Phase 4: Keepa batch fetch — only for available (uncached) ASINs
|
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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...`);
|
||||
try {
|
||||
keepaResults = await fetchKeepaDataBatch(
|
||||
availableProducts.map((p) => p.asin),
|
||||
);
|
||||
} catch (err) {
|
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console.warn(`Keepa batch fetch failed: ${err}`);
|
||||
}
|
||||
}
|
||||
|
||||
// Phase 5: SP-API pricing + fees — only for available ASINs
|
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console.log(
|
||||
`\nFetching pricing & fees for ${availableProducts.length} ASINs...`,
|
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);
|
||||
const spApiResults = new Map<string, SpApiData>();
|
||||
|
||||
// Concurrency-limited pricing+fees fetches
|
||||
const pricingQueue = [...availableProducts];
|
||||
let pricingDone = 0;
|
||||
|
||||
async function fetchNextPricing(): Promise<void> {
|
||||
while (pricingQueue.length > 0) {
|
||||
const p = pricingQueue.shift()!;
|
||||
const sellability = sellabilityMap.get(p.asin)!;
|
||||
const spApi = await fetchSpApiPricingAndFees(p.asin, sellability);
|
||||
|
||||
const keepa = keepaResults.get(p.asin);
|
||||
if (keepa?.currentPrice && spApi.estimatedSalePrice === 0) {
|
||||
spApi.estimatedSalePrice = keepa.currentPrice;
|
||||
}
|
||||
|
||||
spApiResults.set(p.asin, spApi);
|
||||
pricingDone++;
|
||||
if (pricingDone % 10 === 0 || pricingDone === availableProducts.length) {
|
||||
console.log(
|
||||
` [pricing] ${pricingDone}/${availableProducts.length} fetched`,
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const pricingWorkers = Array.from(
|
||||
{ length: Math.min(5, availableProducts.length || 1) },
|
||||
() => fetchNextPricing(),
|
||||
);
|
||||
await Promise.all(pricingWorkers);
|
||||
|
||||
// Phase 6: Build enriched products
|
||||
console.log(`\nEnriching products...`);
|
||||
const enriched: EnrichedProduct[] = [];
|
||||
const availableAsins = new Set(availableProducts.map((ap) => ap.asin));
|
||||
|
||||
for (const p of products) {
|
||||
if (excludedCachedAsins.has(p.asin)) {
|
||||
continue;
|
||||
}
|
||||
|
||||
// Cached products — already enriched
|
||||
const cachedProduct = cached.get(p.asin);
|
||||
if (cachedProduct) {
|
||||
enriched.push(cachedProduct);
|
||||
continue;
|
||||
}
|
||||
|
||||
// Exclude products that are not explicitly available.
|
||||
if (!availableAsins.has(p.asin)) {
|
||||
continue;
|
||||
}
|
||||
|
||||
// Available products — full enrichment
|
||||
const keepa = keepaResults.get(p.asin) ?? null;
|
||||
const spApi = spApiResults.get(p.asin) ?? {
|
||||
fbaFee: 5.0,
|
||||
fbmFee: 1.5,
|
||||
referralFeePercent: 15,
|
||||
estimatedSalePrice: 0,
|
||||
canSell: null,
|
||||
sellabilityStatus: "unknown" as const,
|
||||
sellabilityReason: "SP-API data missing",
|
||||
};
|
||||
|
||||
const product: EnrichedProduct = {
|
||||
record: p,
|
||||
keepa,
|
||||
spApi,
|
||||
fetchedAt: new Date().toISOString(),
|
||||
};
|
||||
|
||||
await setCache(p.asin, product);
|
||||
enriched.push(product);
|
||||
|
||||
if (keepa) {
|
||||
console.log(
|
||||
` [enriched] ${p.asin} — price: $${keepa.currentPrice ?? "N/A"}, rank: ${keepa.salesRank ?? "N/A"}`,
|
||||
);
|
||||
} else {
|
||||
console.log(` [no keepa] ${p.asin} — using spreadsheet data only`);
|
||||
}
|
||||
}
|
||||
|
||||
// Phase 7: LLM analysis in batches — only for enriched available products
|
||||
console.log(
|
||||
`\nAnalyzing ${enriched.length} products via LLM (batch size: ${LLM_BATCH_SIZE})...\n`,
|
||||
);
|
||||
|
||||
const results: AnalysisResult[] = [];
|
||||
for (let i = 0; i < enriched.length; i += LLM_BATCH_SIZE) {
|
||||
const batch = enriched.slice(i, i + LLM_BATCH_SIZE);
|
||||
const batchNum = Math.floor(i / LLM_BATCH_SIZE) + 1;
|
||||
const totalBatches = Math.ceil(enriched.length / LLM_BATCH_SIZE);
|
||||
console.log(` LLM batch ${batchNum}/${totalBatches}...`);
|
||||
|
||||
// Wait between batches to avoid overwhelming LM Studio
|
||||
if (i > 0) {
|
||||
console.log(` Waiting 5s before next batch...`);
|
||||
await new Promise((r) => setTimeout(r, 5000));
|
||||
}
|
||||
|
||||
let verdicts;
|
||||
try {
|
||||
verdicts = await analyzeProducts(batch);
|
||||
} catch {
|
||||
console.warn(` LLM batch error, retrying after 10s...`);
|
||||
await new Promise((r) => setTimeout(r, 10_000));
|
||||
try {
|
||||
verdicts = await analyzeProducts(batch);
|
||||
} catch (retryErr) {
|
||||
console.error(` LLM analysis failed: ${retryErr}`);
|
||||
verdicts = null;
|
||||
}
|
||||
}
|
||||
|
||||
for (let j = 0; j < batch.length; j++) {
|
||||
results.push({
|
||||
product: batch[j]!,
|
||||
verdict: verdicts?.[j] ?? {
|
||||
asin: batch[j]!.record.asin,
|
||||
verdict: "SKIP",
|
||||
confidence: 0,
|
||||
reasoning: "LLM analysis failed",
|
||||
},
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
return results;
|
||||
}
|
||||
|
||||
async function main() {
|
||||
const { inputFile, outputFile } = parseArgs();
|
||||
|
||||
console.log("Connecting to Redis...");
|
||||
await connectCache();
|
||||
|
||||
try {
|
||||
// Phase 1: Read input file
|
||||
console.log(`\nReading ${inputFile}...`);
|
||||
const products = readProducts(inputFile);
|
||||
|
||||
if (products.length === 0) {
|
||||
console.error("No valid products found in input file.");
|
||||
process.exit(1);
|
||||
}
|
||||
|
||||
const productChunks = chunkArray(products, INPUT_BATCH_SIZE);
|
||||
const hasMultipleChunks = productChunks.length > 1;
|
||||
const shouldWriteChunkFiles = hasMultipleChunks;
|
||||
const resolvedBaseOutputPath = resolveBaseOutputPath(inputFile, outputFile);
|
||||
const allResults: AnalysisResult[] = [];
|
||||
|
||||
if (hasMultipleChunks) {
|
||||
console.log(
|
||||
`\nLarge input detected (${products.length} products). Processing in chunks of ${INPUT_BATCH_SIZE}.`,
|
||||
);
|
||||
console.log(
|
||||
`Chunk outputs will be written as numbered files using base: ${resolvedBaseOutputPath}`,
|
||||
);
|
||||
}
|
||||
|
||||
for (let chunkIndex = 0; chunkIndex < productChunks.length; chunkIndex++) {
|
||||
const chunk = productChunks[chunkIndex]!;
|
||||
console.log(
|
||||
`\n=== Input chunk ${chunkIndex + 1}/${productChunks.length} (${chunk.length} products) ===`,
|
||||
);
|
||||
|
||||
const chunkResults = await processProductChunk(chunk);
|
||||
allResults.push(...chunkResults);
|
||||
|
||||
if (shouldWriteChunkFiles) {
|
||||
const chunkOutputPath = buildChunkOutputPath(
|
||||
resolvedBaseOutputPath,
|
||||
chunkIndex,
|
||||
);
|
||||
writeResultsCsv(chunkResults, chunkOutputPath);
|
||||
}
|
||||
}
|
||||
|
||||
printResults(allResults);
|
||||
|
||||
if (!hasMultipleChunks && outputFile) {
|
||||
writeResultsCsv(allResults, outputFile);
|
||||
}
|
||||
} finally {
|
||||
await disconnectCache();
|
||||
}
|
||||
}
|
||||
|
||||
main().catch((err) => {
|
||||
console.error("Fatal error:", err);
|
||||
process.exit(1);
|
||||
});
|
||||
import { readProducts } from "./reader.ts";
|
||||
import { fetchKeepaDataBatch } from "./keepa.ts";
|
||||
import { fetchSellabilityBatch, fetchSpApiPricingAndFees } from "./sp-api.ts";
|
||||
import { connectCache, getCache, setCache, disconnectCache } from "./cache.ts";
|
||||
import { analyzeProducts } from "./llm.ts";
|
||||
import { printResults, writeResultsCsv } from "./writer.ts";
|
||||
import path from "node:path";
|
||||
import type {
|
||||
EnrichedProduct,
|
||||
AnalysisResult,
|
||||
KeepaData,
|
||||
ProductRecord,
|
||||
SellabilityInfo,
|
||||
SpApiData,
|
||||
} from "./types.ts";
|
||||
|
||||
const LLM_BATCH_SIZE = 5;
|
||||
const INPUT_BATCH_SIZE = 50;
|
||||
|
||||
function parseArgs(): { inputFile: string; outputFile?: string } {
|
||||
const args = process.argv.slice(2);
|
||||
const inputFile = args.find((a) => !a.startsWith("--"));
|
||||
const outIdx = args.indexOf("--out");
|
||||
const outputFile = outIdx !== -1 ? args[outIdx + 1] : undefined;
|
||||
|
||||
if (!inputFile) {
|
||||
console.error(
|
||||
"Usage: bun run src/index.ts <input.csv|xlsx> [--out results.csv]",
|
||||
);
|
||||
process.exit(1);
|
||||
}
|
||||
return { inputFile, outputFile };
|
||||
}
|
||||
|
||||
function chunkArray<T>(items: T[], chunkSize: number): T[][] {
|
||||
const chunks: T[][] = [];
|
||||
for (let i = 0; i < items.length; i += chunkSize) {
|
||||
chunks.push(items.slice(i, i + chunkSize));
|
||||
}
|
||||
return chunks;
|
||||
}
|
||||
|
||||
function resolveBaseOutputPath(inputFile: string, outputFile?: string): string {
|
||||
if (outputFile) return outputFile;
|
||||
|
||||
const parsedInput = path.parse(inputFile);
|
||||
return path.join(parsedInput.dir, `${parsedInput.name}_results.xlsx`);
|
||||
}
|
||||
|
||||
function buildChunkOutputPath(
|
||||
baseOutputPath: string,
|
||||
chunkIndex: number,
|
||||
): string {
|
||||
const parsed = path.parse(baseOutputPath);
|
||||
const extension = parsed.ext || ".xlsx";
|
||||
const chunkSuffix = String(chunkIndex + 1).padStart(3, "0");
|
||||
return path.join(
|
||||
parsed.dir,
|
||||
`${parsed.name}_part_${chunkSuffix}${extension}`,
|
||||
);
|
||||
}
|
||||
|
||||
async function processProductChunk(
|
||||
products: ProductRecord[],
|
||||
): Promise<AnalysisResult[]> {
|
||||
// Phase 2: Check cache for all ASINs in chunk
|
||||
console.log(`\nChecking cache for ${products.length} products...`);
|
||||
const cached = new Map<string, EnrichedProduct>();
|
||||
const excludedCachedAsins = new Set<string>();
|
||||
const uncachedProducts: ProductRecord[] = [];
|
||||
|
||||
for (const p of products) {
|
||||
const hit = await getCache(p.asin);
|
||||
if (hit) {
|
||||
if (hit.spApi.sellabilityStatus === "available") {
|
||||
console.log(` [cache hit] ${p.asin}`);
|
||||
cached.set(p.asin, hit);
|
||||
} else {
|
||||
excludedCachedAsins.add(p.asin);
|
||||
console.log(
|
||||
` [exclude cached] ${p.asin} — status=${hit.spApi.sellabilityStatus}`,
|
||||
);
|
||||
}
|
||||
} else {
|
||||
uncachedProducts.push(p);
|
||||
}
|
||||
}
|
||||
console.log(
|
||||
`${cached.size} cached available, ${excludedCachedAsins.size} cached excluded, ${uncachedProducts.length} to fetch`,
|
||||
);
|
||||
|
||||
// Phase 3: Sellability gate — check uncached ASINs before anything else
|
||||
const sellabilityMap = new Map<string, SellabilityInfo>();
|
||||
const availableProducts: ProductRecord[] = [];
|
||||
const unavailableProducts: ProductRecord[] = [];
|
||||
|
||||
if (uncachedProducts.length > 0) {
|
||||
console.log(
|
||||
`\nChecking sellability for ${uncachedProducts.length} ASINs...`,
|
||||
);
|
||||
const sellResults = await fetchSellabilityBatch(
|
||||
uncachedProducts.map((p) => p.asin),
|
||||
);
|
||||
|
||||
for (const p of uncachedProducts) {
|
||||
const info = sellResults.get(p.asin) ?? {
|
||||
canSell: null,
|
||||
sellabilityStatus: "unknown" as const,
|
||||
sellabilityReason: "Sellability check returned no result",
|
||||
};
|
||||
sellabilityMap.set(p.asin, info);
|
||||
|
||||
// Keep only ASINs that are explicitly available.
|
||||
if (info.sellabilityStatus === "available") {
|
||||
availableProducts.push(p);
|
||||
console.log(
|
||||
` [available] ${p.asin} — status=${info.sellabilityStatus}`,
|
||||
);
|
||||
} else {
|
||||
unavailableProducts.push(p);
|
||||
console.log(
|
||||
` [exclude] ${p.asin} — status=${info.sellabilityStatus}, reason=${info.sellabilityReason ?? "n/a"}`,
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
console.log(
|
||||
`\nSellability gate: ${availableProducts.length} available, ${unavailableProducts.length} excluded`,
|
||||
);
|
||||
}
|
||||
|
||||
// Phase 4: Keepa batch fetch — only for available (uncached) ASINs
|
||||
let keepaResults = new Map<string, KeepaData>();
|
||||
if (availableProducts.length > 0) {
|
||||
console.log(`\nFetching ${availableProducts.length} ASINs from Keepa...`);
|
||||
try {
|
||||
keepaResults = await fetchKeepaDataBatch(
|
||||
availableProducts.map((p) => p.asin),
|
||||
);
|
||||
} catch (err) {
|
||||
console.warn(`Keepa batch fetch failed: ${err}`);
|
||||
}
|
||||
}
|
||||
|
||||
// Phase 5: SP-API pricing + fees — only for available ASINs
|
||||
console.log(
|
||||
`\nFetching pricing & fees for ${availableProducts.length} ASINs...`,
|
||||
);
|
||||
const spApiResults = new Map<string, SpApiData>();
|
||||
|
||||
// Concurrency-limited pricing+fees fetches
|
||||
const pricingQueue = [...availableProducts];
|
||||
let pricingDone = 0;
|
||||
|
||||
async function fetchNextPricing(): Promise<void> {
|
||||
while (pricingQueue.length > 0) {
|
||||
const p = pricingQueue.shift()!;
|
||||
const sellability = sellabilityMap.get(p.asin)!;
|
||||
const spApi = await fetchSpApiPricingAndFees(p.asin, sellability);
|
||||
|
||||
const keepa = keepaResults.get(p.asin);
|
||||
if (keepa?.currentPrice && spApi.estimatedSalePrice === 0) {
|
||||
spApi.estimatedSalePrice = keepa.currentPrice;
|
||||
}
|
||||
|
||||
spApiResults.set(p.asin, spApi);
|
||||
pricingDone++;
|
||||
if (pricingDone % 10 === 0 || pricingDone === availableProducts.length) {
|
||||
console.log(
|
||||
` [pricing] ${pricingDone}/${availableProducts.length} fetched`,
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const pricingWorkers = Array.from(
|
||||
{ length: Math.min(5, availableProducts.length || 1) },
|
||||
() => fetchNextPricing(),
|
||||
);
|
||||
await Promise.all(pricingWorkers);
|
||||
|
||||
// Phase 6: Build enriched products
|
||||
console.log(`\nEnriching products...`);
|
||||
const enriched: EnrichedProduct[] = [];
|
||||
const availableAsins = new Set(availableProducts.map((ap) => ap.asin));
|
||||
|
||||
for (const p of products) {
|
||||
if (excludedCachedAsins.has(p.asin)) {
|
||||
continue;
|
||||
}
|
||||
|
||||
// Cached products — already enriched
|
||||
const cachedProduct = cached.get(p.asin);
|
||||
if (cachedProduct) {
|
||||
enriched.push(cachedProduct);
|
||||
continue;
|
||||
}
|
||||
|
||||
// Exclude products that are not explicitly available.
|
||||
if (!availableAsins.has(p.asin)) {
|
||||
continue;
|
||||
}
|
||||
|
||||
// Available products — full enrichment
|
||||
const keepa = keepaResults.get(p.asin) ?? null;
|
||||
const spApi = spApiResults.get(p.asin) ?? {
|
||||
fbaFee: 5.0,
|
||||
fbmFee: 1.5,
|
||||
referralFeePercent: 15,
|
||||
estimatedSalePrice: 0,
|
||||
canSell: null,
|
||||
sellabilityStatus: "unknown" as const,
|
||||
sellabilityReason: "SP-API data missing",
|
||||
};
|
||||
|
||||
const product: EnrichedProduct = {
|
||||
record: p,
|
||||
keepa,
|
||||
spApi,
|
||||
fetchedAt: new Date().toISOString(),
|
||||
};
|
||||
|
||||
await setCache(p.asin, product);
|
||||
enriched.push(product);
|
||||
|
||||
if (keepa) {
|
||||
console.log(
|
||||
` [enriched] ${p.asin} — price: $${keepa.currentPrice ?? "N/A"}, rank: ${keepa.salesRank ?? "N/A"}`,
|
||||
);
|
||||
} else {
|
||||
console.log(` [no keepa] ${p.asin} — using spreadsheet data only`);
|
||||
}
|
||||
}
|
||||
|
||||
// Phase 7: LLM analysis in batches — only for enriched available products
|
||||
console.log(
|
||||
`\nAnalyzing ${enriched.length} products via LLM (batch size: ${LLM_BATCH_SIZE})...\n`,
|
||||
);
|
||||
|
||||
const results: AnalysisResult[] = [];
|
||||
for (let i = 0; i < enriched.length; i += LLM_BATCH_SIZE) {
|
||||
const batch = enriched.slice(i, i + LLM_BATCH_SIZE);
|
||||
const batchNum = Math.floor(i / LLM_BATCH_SIZE) + 1;
|
||||
const totalBatches = Math.ceil(enriched.length / LLM_BATCH_SIZE);
|
||||
console.log(` LLM batch ${batchNum}/${totalBatches}...`);
|
||||
|
||||
// Wait between batches to avoid overwhelming LM Studio
|
||||
if (i > 0) {
|
||||
console.log(` Waiting 5s before next batch...`);
|
||||
await new Promise((r) => setTimeout(r, 5000));
|
||||
}
|
||||
|
||||
let verdicts;
|
||||
try {
|
||||
verdicts = await analyzeProducts(batch);
|
||||
} catch {
|
||||
console.warn(` LLM batch error, retrying after 10s...`);
|
||||
await new Promise((r) => setTimeout(r, 10_000));
|
||||
try {
|
||||
verdicts = await analyzeProducts(batch);
|
||||
} catch (retryErr) {
|
||||
console.error(` LLM analysis failed: ${retryErr}`);
|
||||
verdicts = null;
|
||||
}
|
||||
}
|
||||
|
||||
for (let j = 0; j < batch.length; j++) {
|
||||
results.push({
|
||||
product: batch[j]!,
|
||||
verdict: verdicts?.[j] ?? {
|
||||
asin: batch[j]!.record.asin,
|
||||
verdict: "SKIP",
|
||||
confidence: 0,
|
||||
reasoning: "LLM analysis failed",
|
||||
},
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
return results;
|
||||
}
|
||||
|
||||
async function main() {
|
||||
const { inputFile, outputFile } = parseArgs();
|
||||
|
||||
console.log("Connecting to Redis...");
|
||||
await connectCache();
|
||||
|
||||
try {
|
||||
// Phase 1: Read input file
|
||||
console.log(`\nReading ${inputFile}...`);
|
||||
const products = readProducts(inputFile);
|
||||
|
||||
if (products.length === 0) {
|
||||
console.error("No valid products found in input file.");
|
||||
process.exit(1);
|
||||
}
|
||||
|
||||
const productChunks = chunkArray(products, INPUT_BATCH_SIZE);
|
||||
const hasMultipleChunks = productChunks.length > 1;
|
||||
const shouldWriteChunkFiles = hasMultipleChunks;
|
||||
const resolvedBaseOutputPath = resolveBaseOutputPath(inputFile, outputFile);
|
||||
const allResults: AnalysisResult[] = [];
|
||||
|
||||
if (hasMultipleChunks) {
|
||||
console.log(
|
||||
`\nLarge input detected (${products.length} products). Processing in chunks of ${INPUT_BATCH_SIZE}.`,
|
||||
);
|
||||
console.log(
|
||||
`Chunk outputs will be written as numbered files using base: ${resolvedBaseOutputPath}`,
|
||||
);
|
||||
}
|
||||
|
||||
for (let chunkIndex = 0; chunkIndex < productChunks.length; chunkIndex++) {
|
||||
const chunk = productChunks[chunkIndex]!;
|
||||
console.log(
|
||||
`\n=== Input chunk ${chunkIndex + 1}/${productChunks.length} (${chunk.length} products) ===`,
|
||||
);
|
||||
|
||||
const chunkResults = await processProductChunk(chunk);
|
||||
allResults.push(...chunkResults);
|
||||
|
||||
if (shouldWriteChunkFiles) {
|
||||
const chunkOutputPath = buildChunkOutputPath(
|
||||
resolvedBaseOutputPath,
|
||||
chunkIndex,
|
||||
);
|
||||
writeResultsCsv(chunkResults, chunkOutputPath);
|
||||
}
|
||||
}
|
||||
|
||||
printResults(allResults);
|
||||
|
||||
if (!hasMultipleChunks && outputFile) {
|
||||
writeResultsCsv(allResults, outputFile);
|
||||
}
|
||||
} finally {
|
||||
await disconnectCache();
|
||||
}
|
||||
}
|
||||
|
||||
main().catch((err) => {
|
||||
console.error("Fatal error:", err);
|
||||
process.exit(1);
|
||||
});
|
||||
|
||||
282
src/keepa.ts
282
src/keepa.ts
@@ -1,141 +1,141 @@
|
||||
import { config } from "./config.ts";
|
||||
import type { KeepaData } from "./types.ts";
|
||||
|
||||
const KEEPA_BASE = "https://api.keepa.com";
|
||||
const MAX_ASINS_PER_REQUEST = 100;
|
||||
|
||||
// Token-based rate limiting: Keepa Pro = 1 token/min regeneration.
|
||||
// Each product request costs 1 token regardless of ASIN count (up to 100).
|
||||
// The API response includes tokensLeft and refillRate — we use those to pace.
|
||||
let tokensLeft = 1; // Conservative start; updated from API response
|
||||
let refillRate = 1; // tokens per minute, updated from API response
|
||||
let lastRequestTime = 0;
|
||||
|
||||
async function waitForToken(): Promise<void> {
|
||||
if (tokensLeft > 0) return;
|
||||
|
||||
const elapsed = (Date.now() - lastRequestTime) / 60_000; // minutes
|
||||
const regenerated = Math.floor(elapsed * refillRate);
|
||||
if (regenerated > 0) {
|
||||
tokensLeft += regenerated;
|
||||
return;
|
||||
}
|
||||
|
||||
// Wait until we regenerate at least 1 token
|
||||
const waitMs =
|
||||
Math.ceil((1 / refillRate) * 60_000) - (Date.now() - lastRequestTime);
|
||||
if (waitMs > 0) {
|
||||
console.log(
|
||||
`Keepa tokens exhausted. Waiting ${Math.ceil(waitMs / 1000)}s for token regeneration...`,
|
||||
);
|
||||
await new Promise((r) => setTimeout(r, waitMs));
|
||||
}
|
||||
tokensLeft = 1;
|
||||
}
|
||||
|
||||
export async function fetchKeepaDataBatch(
|
||||
asins: string[],
|
||||
): Promise<Map<string, KeepaData>> {
|
||||
const results = new Map<string, KeepaData>();
|
||||
|
||||
// Split into chunks of MAX_ASINS_PER_REQUEST
|
||||
for (let i = 0; i < asins.length; i += MAX_ASINS_PER_REQUEST) {
|
||||
const chunk = asins.slice(i, i + MAX_ASINS_PER_REQUEST);
|
||||
await waitForToken();
|
||||
|
||||
const asinParam = chunk.join(",");
|
||||
const url = `${KEEPA_BASE}/product?key=${config.keepaApiKey}&domain=1&asin=${asinParam}&stats=90`;
|
||||
|
||||
console.log(
|
||||
`Keepa: fetching ${chunk.length} ASINs (tokens left: ${tokensLeft})...`,
|
||||
);
|
||||
|
||||
const res = await fetch(url);
|
||||
lastRequestTime = Date.now();
|
||||
|
||||
if (!res.ok) {
|
||||
const text = await res.text();
|
||||
throw new Error(`Keepa API error ${res.status}: ${text}`);
|
||||
}
|
||||
|
||||
const data = (await res.json()) as {
|
||||
products?: Record<string, any>[];
|
||||
tokensLeft?: number;
|
||||
refillRate?: number;
|
||||
};
|
||||
|
||||
// Update token state from API response
|
||||
if (data.tokensLeft != null) tokensLeft = data.tokensLeft;
|
||||
if (data.refillRate != null) refillRate = data.refillRate;
|
||||
|
||||
console.log(
|
||||
`Keepa: ${data.products?.length ?? 0} products returned, ${tokensLeft} tokens remaining (refill: ${refillRate}/min)`,
|
||||
);
|
||||
|
||||
if (data.products) {
|
||||
for (const product of data.products) {
|
||||
const asin = product.asin;
|
||||
if (!asin) continue;
|
||||
results.set(asin, parseKeepaProduct(product));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return results;
|
||||
}
|
||||
|
||||
function parseKeepaProduct(product: Record<string, any>): KeepaData {
|
||||
const stats = product.stats;
|
||||
const csv = product.csv;
|
||||
const salesRankDrops30 = pickKeepaNumber(
|
||||
product.salesRankDrops30,
|
||||
stats?.salesRankDrops30,
|
||||
);
|
||||
const salesRankDrops90 =
|
||||
pickKeepaNumber(product.salesRankDrops90, stats?.salesRankDrops90) ??
|
||||
(salesRankDrops30 != null ? salesRankDrops30 * 3 : null);
|
||||
const monthlySold =
|
||||
pickKeepaNumber(product.monthlySold, stats?.monthlySold) ??
|
||||
salesRankDrops30;
|
||||
|
||||
return {
|
||||
currentPrice: extractCurrentPrice(csv),
|
||||
avgPrice90: stats?.avg?.[0] != null ? stats.avg[0] / 100 : null,
|
||||
minPrice90: stats?.min?.[0] != null ? stats.min[0] / 100 : null,
|
||||
maxPrice90: stats?.max?.[0] != null ? stats.max[0] / 100 : null,
|
||||
salesRank: stats?.current?.[3] ?? null,
|
||||
salesRankAvg90: stats?.avg?.[3] ?? null,
|
||||
salesRankDrops30,
|
||||
salesRankDrops90,
|
||||
sellerCount: stats?.current?.[11] ?? null,
|
||||
buyBoxSeller: product.buyBoxSellerId ?? null,
|
||||
buyBoxPrice: stats?.current?.[18] != null ? stats.current[18] / 100 : null,
|
||||
monthlySold,
|
||||
categoryTree:
|
||||
product.categoryTree?.map((c: { name: string }) => c.name) ?? [],
|
||||
};
|
||||
}
|
||||
|
||||
function pickKeepaNumber(...values: unknown[]): number | null {
|
||||
for (const value of values) {
|
||||
if (typeof value !== "number" || !Number.isFinite(value)) continue;
|
||||
// Keepa often uses -1 as "not available".
|
||||
if (value < 0) continue;
|
||||
return value;
|
||||
}
|
||||
return null;
|
||||
}
|
||||
|
||||
function extractCurrentPrice(csv: number[][] | undefined): number | null {
|
||||
if (!csv) return null;
|
||||
|
||||
// csv[0] = Amazon price history, csv[1] = Marketplace new price history
|
||||
// Each is [time, price, time, price, ...] — last value is most recent
|
||||
for (const series of [csv[0], csv[1]]) {
|
||||
if (series && series.length >= 2) {
|
||||
const lastPrice = series[series.length - 1]!;
|
||||
if (lastPrice > 0) return lastPrice / 100;
|
||||
}
|
||||
}
|
||||
return null;
|
||||
}
|
||||
import { config } from "./config.ts";
|
||||
import type { KeepaData } from "./types.ts";
|
||||
|
||||
const KEEPA_BASE = "https://api.keepa.com";
|
||||
const MAX_ASINS_PER_REQUEST = 100;
|
||||
|
||||
// Token-based rate limiting: Keepa Pro = 1 token/min regeneration.
|
||||
// Each product request costs 1 token regardless of ASIN count (up to 100).
|
||||
// The API response includes tokensLeft and refillRate — we use those to pace.
|
||||
let tokensLeft = 1; // Conservative start; updated from API response
|
||||
let refillRate = 1; // tokens per minute, updated from API response
|
||||
let lastRequestTime = 0;
|
||||
|
||||
async function waitForToken(): Promise<void> {
|
||||
if (tokensLeft > 0) return;
|
||||
|
||||
const elapsed = (Date.now() - lastRequestTime) / 60_000; // minutes
|
||||
const regenerated = Math.floor(elapsed * refillRate);
|
||||
if (regenerated > 0) {
|
||||
tokensLeft += regenerated;
|
||||
return;
|
||||
}
|
||||
|
||||
// Wait until we regenerate at least 1 token
|
||||
const waitMs =
|
||||
Math.ceil((1 / refillRate) * 60_000) - (Date.now() - lastRequestTime);
|
||||
if (waitMs > 0) {
|
||||
console.log(
|
||||
`Keepa tokens exhausted. Waiting ${Math.ceil(waitMs / 1000)}s for token regeneration...`,
|
||||
);
|
||||
await new Promise((r) => setTimeout(r, waitMs));
|
||||
}
|
||||
tokensLeft = 1;
|
||||
}
|
||||
|
||||
export async function fetchKeepaDataBatch(
|
||||
asins: string[],
|
||||
): Promise<Map<string, KeepaData>> {
|
||||
const results = new Map<string, KeepaData>();
|
||||
|
||||
// Split into chunks of MAX_ASINS_PER_REQUEST
|
||||
for (let i = 0; i < asins.length; i += MAX_ASINS_PER_REQUEST) {
|
||||
const chunk = asins.slice(i, i + MAX_ASINS_PER_REQUEST);
|
||||
await waitForToken();
|
||||
|
||||
const asinParam = chunk.join(",");
|
||||
const url = `${KEEPA_BASE}/product?key=${config.keepaApiKey}&domain=1&asin=${asinParam}&stats=90`;
|
||||
|
||||
console.log(
|
||||
`Keepa: fetching ${chunk.length} ASINs (tokens left: ${tokensLeft})...`,
|
||||
);
|
||||
|
||||
const res = await fetch(url);
|
||||
lastRequestTime = Date.now();
|
||||
|
||||
if (!res.ok) {
|
||||
const text = await res.text();
|
||||
throw new Error(`Keepa API error ${res.status}: ${text}`);
|
||||
}
|
||||
|
||||
const data = (await res.json()) as {
|
||||
products?: Record<string, any>[];
|
||||
tokensLeft?: number;
|
||||
refillRate?: number;
|
||||
};
|
||||
|
||||
// Update token state from API response
|
||||
if (data.tokensLeft != null) tokensLeft = data.tokensLeft;
|
||||
if (data.refillRate != null) refillRate = data.refillRate;
|
||||
|
||||
console.log(
|
||||
`Keepa: ${data.products?.length ?? 0} products returned, ${tokensLeft} tokens remaining (refill: ${refillRate}/min)`,
|
||||
);
|
||||
|
||||
if (data.products) {
|
||||
for (const product of data.products) {
|
||||
const asin = product.asin;
|
||||
if (!asin) continue;
|
||||
results.set(asin, parseKeepaProduct(product));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return results;
|
||||
}
|
||||
|
||||
function parseKeepaProduct(product: Record<string, any>): KeepaData {
|
||||
const stats = product.stats;
|
||||
const csv = product.csv;
|
||||
const salesRankDrops30 = pickKeepaNumber(
|
||||
product.salesRankDrops30,
|
||||
stats?.salesRankDrops30,
|
||||
);
|
||||
const salesRankDrops90 =
|
||||
pickKeepaNumber(product.salesRankDrops90, stats?.salesRankDrops90) ??
|
||||
(salesRankDrops30 != null ? salesRankDrops30 * 3 : null);
|
||||
const monthlySold =
|
||||
pickKeepaNumber(product.monthlySold, stats?.monthlySold) ??
|
||||
salesRankDrops30;
|
||||
|
||||
return {
|
||||
currentPrice: extractCurrentPrice(csv),
|
||||
avgPrice90: stats?.avg?.[0] != null ? stats.avg[0] / 100 : null,
|
||||
minPrice90: stats?.min?.[0] != null ? stats.min[0] / 100 : null,
|
||||
maxPrice90: stats?.max?.[0] != null ? stats.max[0] / 100 : null,
|
||||
salesRank: stats?.current?.[3] ?? null,
|
||||
salesRankAvg90: stats?.avg?.[3] ?? null,
|
||||
salesRankDrops30,
|
||||
salesRankDrops90,
|
||||
sellerCount: stats?.current?.[11] ?? null,
|
||||
buyBoxSeller: product.buyBoxSellerId ?? null,
|
||||
buyBoxPrice: stats?.current?.[18] != null ? stats.current[18] / 100 : null,
|
||||
monthlySold,
|
||||
categoryTree:
|
||||
product.categoryTree?.map((c: { name: string }) => c.name) ?? [],
|
||||
};
|
||||
}
|
||||
|
||||
function pickKeepaNumber(...values: unknown[]): number | null {
|
||||
for (const value of values) {
|
||||
if (typeof value !== "number" || !Number.isFinite(value)) continue;
|
||||
// Keepa often uses -1 as "not available".
|
||||
if (value < 0) continue;
|
||||
return value;
|
||||
}
|
||||
return null;
|
||||
}
|
||||
|
||||
function extractCurrentPrice(csv: number[][] | undefined): number | null {
|
||||
if (!csv) return null;
|
||||
|
||||
// csv[0] = Amazon price history, csv[1] = Marketplace new price history
|
||||
// Each is [time, price, time, price, ...] — last value is most recent
|
||||
for (const series of [csv[0], csv[1]]) {
|
||||
if (series && series.length >= 2) {
|
||||
const lastPrice = series[series.length - 1]!;
|
||||
if (lastPrice > 0) return lastPrice / 100;
|
||||
}
|
||||
}
|
||||
return null;
|
||||
}
|
||||
|
||||
706
src/llm.ts
706
src/llm.ts
@@ -1,353 +1,353 @@
|
||||
import { config } from "./config.ts";
|
||||
import type { EnrichedProduct, LlmVerdict } from "./types.ts";
|
||||
|
||||
const SYSTEM_PROMPT = `You are an expert Amazon product analyst specializing in FBA and FBM fulfillment strategy.
|
||||
|
||||
Given product data, evaluate each product's viability for selling on Amazon. Consider:
|
||||
|
||||
1. **Sales Velocity**: monthlySold and salesRankDrops30 are the most important signals. A product that doesn't sell is worthless regardless of margin. salesRankDrops30 = approximate units sold in 30 days. monthlySold is Keepa's estimate.
|
||||
2. **Margin Analysis**: Sale price minus unit cost minus fees (FBA or FBM). Aim for >30% ROI minimum. The spreadsheet may include FBA NET and gross profit estimates — cross-check against Keepa pricing data.
|
||||
3. **Sales Rank (BSR)**: Lower rank = higher demand. Rank <50,000 is good, <1,000 is excellent.
|
||||
4. **Sales Rank Trend**: Compare current rank vs 90d average. Lower current = improving demand.
|
||||
5. **Competition**: Number of sellers and Buy Box dynamics. Fewer sellers = easier entry.
|
||||
6. **Price Stability**: Large price swings (high max vs low min over 90d) = volatile/risky.
|
||||
7. **FBA vs FBM**: FBA preferred for fast-selling, small/light items. FBM for oversized, slow-moving, or high-margin items where fee savings matter.
|
||||
8. **MOQ & Capital**: High MOQ with thin margins is risky.
|
||||
9. **Supply Availability**: Total quantity available from supplier — low stock means limited runway.
|
||||
10. **Seller Eligibility (critical)**:
|
||||
- If sellerEligibility.status is "restricted" or "not_available", return verdict = "SKIP".
|
||||
- If sellerEligibility.status is "unknown", treat as elevated risk and only allow FBA/FBM with clearly strong economics + demand.
|
||||
- If canSell is false, return "SKIP" regardless of margin.
|
||||
|
||||
Decision policy:
|
||||
- Do not recommend products that cannot be listed by this seller account.
|
||||
- Prioritize profitable + high-velocity + listable products.
|
||||
- Use "SKIP" when data quality is poor or risk is high.
|
||||
|
||||
Return ONLY a raw JSON array (no markdown, no code fences, no explanation before or after). One verdict per product:
|
||||
[{ "asin": "B...", "verdict": "FBA" | "FBM" | "SKIP", "confidence": 0-100, "reasoning": "..." }]
|
||||
|
||||
Keep each reasoning under 100 characters to stay within output limits and mention key blocker if skipped (e.g., restricted, low demand, thin margin).`;
|
||||
|
||||
export async function analyzeProducts(
|
||||
products: EnrichedProduct[],
|
||||
): Promise<LlmVerdict[]> {
|
||||
try {
|
||||
return await analyzeProductsInternal(products);
|
||||
} catch (err) {
|
||||
const msg = String(err);
|
||||
if (products.length > 1 && msg.includes("Context size has been exceeded")) {
|
||||
console.warn(
|
||||
`LLM context exceeded for batch of ${products.length}, retrying one product at a time...`,
|
||||
);
|
||||
|
||||
const fallback: LlmVerdict[] = [];
|
||||
for (const product of products) {
|
||||
try {
|
||||
const single = await analyzeProductsInternal([product]);
|
||||
fallback.push(
|
||||
single[0] ?? {
|
||||
asin: product.record.asin,
|
||||
verdict: "SKIP",
|
||||
confidence: 0,
|
||||
reasoning: "LLM returned empty verdict",
|
||||
},
|
||||
);
|
||||
} catch {
|
||||
fallback.push({
|
||||
asin: product.record.asin,
|
||||
verdict: "SKIP",
|
||||
confidence: 0,
|
||||
reasoning: "LLM context overflow on single-item fallback",
|
||||
});
|
||||
}
|
||||
}
|
||||
return fallback;
|
||||
}
|
||||
throw err;
|
||||
}
|
||||
}
|
||||
|
||||
async function analyzeProductsInternal(
|
||||
products: EnrichedProduct[],
|
||||
): Promise<LlmVerdict[]> {
|
||||
const productSummaries = products.map(summarizeForLlm);
|
||||
|
||||
const res = await fetch(`${config.llmUrl}/chat/completions`, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
Authorization: "Bearer lm-studio",
|
||||
},
|
||||
body: JSON.stringify({
|
||||
model: config.llmModel,
|
||||
messages: [
|
||||
{ role: "system", content: SYSTEM_PROMPT },
|
||||
{ role: "user", content: JSON.stringify(productSummaries, null, 2) },
|
||||
],
|
||||
temperature: 0.3,
|
||||
max_tokens: 2048,
|
||||
}),
|
||||
});
|
||||
|
||||
if (!res.ok) {
|
||||
throw new Error(`LLM API error ${res.status}: ${await res.text()}`);
|
||||
}
|
||||
|
||||
const data = (await res.json()) as {
|
||||
choices?: { message?: { content?: string } }[];
|
||||
};
|
||||
const content = data.choices?.[0]?.message?.content ?? "";
|
||||
|
||||
return parseVerdicts(content, products);
|
||||
}
|
||||
|
||||
function summarizeForLlm(p: EnrichedProduct) {
|
||||
const salePrice =
|
||||
p.keepa?.currentPrice ??
|
||||
p.record.sellingPriceFromSheet ??
|
||||
p.spApi.estimatedSalePrice;
|
||||
const referralFee = salePrice * (p.spApi.referralFeePercent / 100);
|
||||
const fbaProfit =
|
||||
salePrice - p.record.unitCost - p.spApi.fbaFee - referralFee;
|
||||
const fbmProfit =
|
||||
salePrice - p.record.unitCost - p.spApi.fbmFee - referralFee;
|
||||
|
||||
return {
|
||||
asin: p.record.asin,
|
||||
name: clampText(p.record.name, 80),
|
||||
brand: p.record.brand,
|
||||
category: clampText(
|
||||
p.record.category ?? p.keepa?.categoryTree?.join(" > "),
|
||||
60,
|
||||
),
|
||||
unitCost: p.record.unitCost,
|
||||
currentPrice: salePrice,
|
||||
priceRange90d: p.keepa
|
||||
? {
|
||||
min: p.keepa.minPrice90,
|
||||
max: p.keepa.maxPrice90,
|
||||
avg: p.keepa.avgPrice90,
|
||||
}
|
||||
: null,
|
||||
salesRank: p.keepa?.salesRank ?? p.record.amazonRank,
|
||||
salesRankAvg90d: p.keepa?.salesRankAvg90,
|
||||
sellerCount: p.keepa?.sellerCount,
|
||||
salesVelocity: {
|
||||
monthlySold: p.keepa?.monthlySold,
|
||||
salesRankDrops30: p.keepa?.salesRankDrops30,
|
||||
salesRankDrops90: p.keepa?.salesRankDrops90,
|
||||
},
|
||||
spreadsheetEstimates: {
|
||||
avgPrice90: p.record.avgPrice90FromSheet,
|
||||
sellingPrice: p.record.sellingPriceFromSheet,
|
||||
fbaNet: p.record.fbaNet,
|
||||
grossProfit: p.record.grossProfit,
|
||||
grossProfitPct: p.record.grossProfitPct,
|
||||
netProfit: p.record.netProfitFromSheet,
|
||||
roi: p.record.roiFromSheet,
|
||||
},
|
||||
supplier: clampText(p.record.supplier, 40),
|
||||
moq: p.record.moq,
|
||||
moqCost: p.record.moqCost,
|
||||
totalQtyAvail: p.record.totalQtyAvail,
|
||||
fees: {
|
||||
fbaFee: p.spApi.fbaFee,
|
||||
fbmFee: p.spApi.fbmFee,
|
||||
referralFeePercent: p.spApi.referralFeePercent,
|
||||
referralFee: Math.round(referralFee * 100) / 100,
|
||||
},
|
||||
sellerEligibility: {
|
||||
canSell: p.spApi.canSell,
|
||||
status: p.spApi.sellabilityStatus,
|
||||
reason: clampText(p.spApi.sellabilityReason, 120),
|
||||
},
|
||||
estimatedProfit: {
|
||||
fba: Math.round(fbaProfit * 100) / 100,
|
||||
fbm: Math.round(fbmProfit * 100) / 100,
|
||||
},
|
||||
estimatedROI: {
|
||||
fba:
|
||||
p.record.unitCost > 0
|
||||
? Math.round((fbaProfit / p.record.unitCost) * 100)
|
||||
: null,
|
||||
fbm:
|
||||
p.record.unitCost > 0
|
||||
? Math.round((fbmProfit / p.record.unitCost) * 100)
|
||||
: null,
|
||||
},
|
||||
};
|
||||
}
|
||||
|
||||
function clampText(value: unknown, maxLen: number): string | undefined {
|
||||
if (value == null) return undefined;
|
||||
const s = String(value).trim();
|
||||
if (!s) return undefined;
|
||||
return s.length > maxLen ? `${s.slice(0, maxLen - 1)}.` : s;
|
||||
}
|
||||
|
||||
function cleanLlmJson(text: string): string {
|
||||
// Remove ```json ... ``` or ``` ... ``` wrapping
|
||||
const fenceMatch = text.match(/```(?:json)?\s*\n?([\s\S]*?)```/);
|
||||
let cleaned = fenceMatch ? fenceMatch[1]!.trim() : text.trim();
|
||||
|
||||
// Strip any non-JSON wrapper text by taking the largest JSON-looking segment
|
||||
const firstArray = cleaned.indexOf("[");
|
||||
const firstObject = cleaned.indexOf("{");
|
||||
const startCandidates = [firstArray, firstObject].filter((i) => i >= 0);
|
||||
const start = startCandidates.length > 0 ? Math.min(...startCandidates) : -1;
|
||||
const endArray = cleaned.lastIndexOf("]");
|
||||
const endObject = cleaned.lastIndexOf("}");
|
||||
const end = Math.max(endArray, endObject);
|
||||
if (start >= 0 && end > start) {
|
||||
cleaned = cleaned.slice(start, end + 1);
|
||||
}
|
||||
|
||||
// Fix trailing comma-quote before closing brace: ,"} → "}
|
||||
cleaned = cleaned.replace(/,"\s*}/g, '"}');
|
||||
|
||||
// Fix malformed comma-quote before a closing bracket/brace: ,"} or ,"]
|
||||
cleaned = cleaned.replace(/,\s*"\s*([}\]])/g, "$1");
|
||||
|
||||
// Fix malformed quote-comma before a closing bracket/brace: ",} or ",]
|
||||
cleaned = cleaned.replace(/"\s*,\s*([}\]])/g, '"$1');
|
||||
|
||||
// Fix trailing commas before ] or }
|
||||
cleaned = cleaned.replace(/,\s*([}\]])/g, "$1");
|
||||
|
||||
return cleaned;
|
||||
}
|
||||
|
||||
function parseVerdicts(
|
||||
content: string,
|
||||
products: EnrichedProduct[],
|
||||
): LlmVerdict[] {
|
||||
const cleaned = cleanLlmJson(content);
|
||||
|
||||
try {
|
||||
const parsed = JSON.parse(cleaned) as unknown;
|
||||
return alignVerdicts(products, normalizeVerdicts(parsed));
|
||||
} catch (err) {
|
||||
const salvaged = extractVerdictsLoosely(cleaned);
|
||||
if (salvaged.length > 0) {
|
||||
console.warn(
|
||||
`LLM response was invalid JSON; salvaged ${salvaged.length} verdict(s) with loose parsing.`,
|
||||
);
|
||||
return alignVerdicts(products, salvaged);
|
||||
}
|
||||
|
||||
console.warn(
|
||||
"Failed to parse LLM response, marking all as ANALYSIS_FAILED",
|
||||
);
|
||||
console.warn("Raw LLM content:", content.slice(0, 500));
|
||||
return products.map((p) => ({
|
||||
asin: p.record.asin,
|
||||
verdict: "SKIP" as const,
|
||||
confidence: 0,
|
||||
reasoning: `Analysis failed: could not parse LLM output`,
|
||||
}));
|
||||
}
|
||||
}
|
||||
|
||||
function normalizeVerdicts(parsed: unknown): LlmVerdict[] {
|
||||
const container =
|
||||
parsed && typeof parsed === "object"
|
||||
? (parsed as Record<string, unknown>)
|
||||
: undefined;
|
||||
const nested = container?.verdicts ?? container?.results;
|
||||
|
||||
const arr: unknown[] = Array.isArray(parsed)
|
||||
? parsed
|
||||
: Array.isArray(nested)
|
||||
? nested
|
||||
: [parsed];
|
||||
|
||||
return arr
|
||||
.filter((v): v is Record<string, unknown> => !!v && typeof v === "object")
|
||||
.map((v) => ({
|
||||
asin: String(v.asin ?? "")
|
||||
.trim()
|
||||
.toUpperCase(),
|
||||
verdict: (String(v.verdict).toUpperCase() === "FBA" ||
|
||||
String(v.verdict).toUpperCase() === "FBM" ||
|
||||
String(v.verdict).toUpperCase() === "SKIP"
|
||||
? String(v.verdict).toUpperCase()
|
||||
: "SKIP") as LlmVerdict["verdict"],
|
||||
confidence: clampConfidence(
|
||||
typeof v.confidence === "number"
|
||||
? v.confidence
|
||||
: Number(v.confidence ?? 0),
|
||||
),
|
||||
reasoning: String(v.reasoning ?? "No reasoning provided"),
|
||||
}));
|
||||
}
|
||||
|
||||
function extractVerdictsLoosely(text: string): LlmVerdict[] {
|
||||
const objectMatches = text.match(/\{[\s\S]*?\}/g) ?? [];
|
||||
const verdicts: LlmVerdict[] = [];
|
||||
|
||||
for (const chunk of objectMatches) {
|
||||
const asin = extractField(chunk, /"asin"\s*:\s*"?([A-Z0-9]{10})"?/i) ?? "";
|
||||
const verdictRaw =
|
||||
extractField(chunk, /"verdict"\s*:\s*"?([A-Z]+)"?/i) ?? "SKIP";
|
||||
const confidenceRaw =
|
||||
extractField(chunk, /"confidence"\s*:\s*([0-9]+(?:\.[0-9]+)?)/i) ?? "0";
|
||||
const reasoning =
|
||||
extractField(chunk, /"reasoning"\s*:\s*"([\s\S]*?)"\s*(?:,|})/i) ??
|
||||
"No reasoning provided";
|
||||
|
||||
const normalizedVerdict = verdictRaw.toUpperCase();
|
||||
if (!asin) continue;
|
||||
|
||||
verdicts.push({
|
||||
asin,
|
||||
verdict: (normalizedVerdict === "FBA" ||
|
||||
normalizedVerdict === "FBM" ||
|
||||
normalizedVerdict === "SKIP"
|
||||
? normalizedVerdict
|
||||
: "SKIP") as LlmVerdict["verdict"],
|
||||
confidence: clampConfidence(Number(confidenceRaw)),
|
||||
reasoning,
|
||||
});
|
||||
}
|
||||
|
||||
return verdicts;
|
||||
}
|
||||
|
||||
function extractField(text: string, regex: RegExp): string | undefined {
|
||||
const match = text.match(regex);
|
||||
return match?.[1]?.trim();
|
||||
}
|
||||
|
||||
function clampConfidence(value: number): number {
|
||||
if (!Number.isFinite(value)) return 0;
|
||||
return Math.max(0, Math.min(100, Math.round(value)));
|
||||
}
|
||||
|
||||
function alignVerdicts(
|
||||
products: EnrichedProduct[],
|
||||
verdicts: LlmVerdict[],
|
||||
): LlmVerdict[] {
|
||||
const byAsin = new Map<string, LlmVerdict>();
|
||||
for (const verdict of verdicts) {
|
||||
if (verdict.asin && !byAsin.has(verdict.asin)) {
|
||||
byAsin.set(verdict.asin, verdict);
|
||||
}
|
||||
}
|
||||
|
||||
return products.map((product, index) => {
|
||||
const asin = product.record.asin;
|
||||
const byAsinVerdict = byAsin.get(asin);
|
||||
if (byAsinVerdict) return { ...byAsinVerdict, asin };
|
||||
|
||||
const byIndexVerdict = verdicts[index];
|
||||
if (byIndexVerdict) return { ...byIndexVerdict, asin };
|
||||
|
||||
return {
|
||||
asin,
|
||||
verdict: "SKIP" as const,
|
||||
confidence: 0,
|
||||
reasoning: "LLM returned no verdict for this product",
|
||||
};
|
||||
});
|
||||
}
|
||||
import { config } from "./config.ts";
|
||||
import type { EnrichedProduct, LlmVerdict } from "./types.ts";
|
||||
|
||||
const SYSTEM_PROMPT = `You are an expert Amazon product analyst specializing in FBA and FBM fulfillment strategy.
|
||||
|
||||
Given product data, evaluate each product's viability for selling on Amazon. Consider:
|
||||
|
||||
1. **Sales Velocity**: monthlySold and salesRankDrops30 are the most important signals. A product that doesn't sell is worthless regardless of margin. salesRankDrops30 = approximate units sold in 30 days. monthlySold is Keepa's estimate.
|
||||
2. **Margin Analysis**: Sale price minus unit cost minus fees (FBA or FBM). Aim for >30% ROI minimum. The spreadsheet may include FBA NET and gross profit estimates — cross-check against Keepa pricing data.
|
||||
3. **Sales Rank (BSR)**: Lower rank = higher demand. Rank <50,000 is good, <1,000 is excellent.
|
||||
4. **Sales Rank Trend**: Compare current rank vs 90d average. Lower current = improving demand.
|
||||
5. **Competition**: Number of sellers and Buy Box dynamics. Fewer sellers = easier entry.
|
||||
6. **Price Stability**: Large price swings (high max vs low min over 90d) = volatile/risky.
|
||||
7. **FBA vs FBM**: FBA preferred for fast-selling, small/light items. FBM for oversized, slow-moving, or high-margin items where fee savings matter.
|
||||
8. **MOQ & Capital**: High MOQ with thin margins is risky.
|
||||
9. **Supply Availability**: Total quantity available from supplier — low stock means limited runway.
|
||||
10. **Seller Eligibility (critical)**:
|
||||
- If sellerEligibility.status is "restricted" or "not_available", return verdict = "SKIP".
|
||||
- If sellerEligibility.status is "unknown", treat as elevated risk and only allow FBA/FBM with clearly strong economics + demand.
|
||||
- If canSell is false, return "SKIP" regardless of margin.
|
||||
|
||||
Decision policy:
|
||||
- Do not recommend products that cannot be listed by this seller account.
|
||||
- Prioritize profitable + high-velocity + listable products.
|
||||
- Use "SKIP" when data quality is poor or risk is high.
|
||||
|
||||
Return ONLY a raw JSON array (no markdown, no code fences, no explanation before or after). One verdict per product:
|
||||
[{ "asin": "B...", "verdict": "FBA" | "FBM" | "SKIP", "confidence": 0-100, "reasoning": "..." }]
|
||||
|
||||
Keep each reasoning under 100 characters to stay within output limits and mention key blocker if skipped (e.g., restricted, low demand, thin margin).`;
|
||||
|
||||
export async function analyzeProducts(
|
||||
products: EnrichedProduct[],
|
||||
): Promise<LlmVerdict[]> {
|
||||
try {
|
||||
return await analyzeProductsInternal(products);
|
||||
} catch (err) {
|
||||
const msg = String(err);
|
||||
if (products.length > 1 && msg.includes("Context size has been exceeded")) {
|
||||
console.warn(
|
||||
`LLM context exceeded for batch of ${products.length}, retrying one product at a time...`,
|
||||
);
|
||||
|
||||
const fallback: LlmVerdict[] = [];
|
||||
for (const product of products) {
|
||||
try {
|
||||
const single = await analyzeProductsInternal([product]);
|
||||
fallback.push(
|
||||
single[0] ?? {
|
||||
asin: product.record.asin,
|
||||
verdict: "SKIP",
|
||||
confidence: 0,
|
||||
reasoning: "LLM returned empty verdict",
|
||||
},
|
||||
);
|
||||
} catch {
|
||||
fallback.push({
|
||||
asin: product.record.asin,
|
||||
verdict: "SKIP",
|
||||
confidence: 0,
|
||||
reasoning: "LLM context overflow on single-item fallback",
|
||||
});
|
||||
}
|
||||
}
|
||||
return fallback;
|
||||
}
|
||||
throw err;
|
||||
}
|
||||
}
|
||||
|
||||
async function analyzeProductsInternal(
|
||||
products: EnrichedProduct[],
|
||||
): Promise<LlmVerdict[]> {
|
||||
const productSummaries = products.map(summarizeForLlm);
|
||||
|
||||
const res = await fetch(`${config.llmUrl}/chat/completions`, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
Authorization: "Bearer lm-studio",
|
||||
},
|
||||
body: JSON.stringify({
|
||||
model: config.llmModel,
|
||||
messages: [
|
||||
{ role: "system", content: SYSTEM_PROMPT },
|
||||
{ role: "user", content: JSON.stringify(productSummaries, null, 2) },
|
||||
],
|
||||
temperature: 0.3,
|
||||
max_tokens: 2048,
|
||||
}),
|
||||
});
|
||||
|
||||
if (!res.ok) {
|
||||
throw new Error(`LLM API error ${res.status}: ${await res.text()}`);
|
||||
}
|
||||
|
||||
const data = (await res.json()) as {
|
||||
choices?: { message?: { content?: string } }[];
|
||||
};
|
||||
const content = data.choices?.[0]?.message?.content ?? "";
|
||||
|
||||
return parseVerdicts(content, products);
|
||||
}
|
||||
|
||||
function summarizeForLlm(p: EnrichedProduct) {
|
||||
const salePrice =
|
||||
p.keepa?.currentPrice ??
|
||||
p.record.sellingPriceFromSheet ??
|
||||
p.spApi.estimatedSalePrice;
|
||||
const referralFee = salePrice * (p.spApi.referralFeePercent / 100);
|
||||
const fbaProfit =
|
||||
salePrice - p.record.unitCost - p.spApi.fbaFee - referralFee;
|
||||
const fbmProfit =
|
||||
salePrice - p.record.unitCost - p.spApi.fbmFee - referralFee;
|
||||
|
||||
return {
|
||||
asin: p.record.asin,
|
||||
name: clampText(p.record.name, 80),
|
||||
brand: p.record.brand,
|
||||
category: clampText(
|
||||
p.record.category ?? p.keepa?.categoryTree?.join(" > "),
|
||||
60,
|
||||
),
|
||||
unitCost: p.record.unitCost,
|
||||
currentPrice: salePrice,
|
||||
priceRange90d: p.keepa
|
||||
? {
|
||||
min: p.keepa.minPrice90,
|
||||
max: p.keepa.maxPrice90,
|
||||
avg: p.keepa.avgPrice90,
|
||||
}
|
||||
: null,
|
||||
salesRank: p.keepa?.salesRank ?? p.record.amazonRank,
|
||||
salesRankAvg90d: p.keepa?.salesRankAvg90,
|
||||
sellerCount: p.keepa?.sellerCount,
|
||||
salesVelocity: {
|
||||
monthlySold: p.keepa?.monthlySold,
|
||||
salesRankDrops30: p.keepa?.salesRankDrops30,
|
||||
salesRankDrops90: p.keepa?.salesRankDrops90,
|
||||
},
|
||||
spreadsheetEstimates: {
|
||||
avgPrice90: p.record.avgPrice90FromSheet,
|
||||
sellingPrice: p.record.sellingPriceFromSheet,
|
||||
fbaNet: p.record.fbaNet,
|
||||
grossProfit: p.record.grossProfit,
|
||||
grossProfitPct: p.record.grossProfitPct,
|
||||
netProfit: p.record.netProfitFromSheet,
|
||||
roi: p.record.roiFromSheet,
|
||||
},
|
||||
supplier: clampText(p.record.supplier, 40),
|
||||
moq: p.record.moq,
|
||||
moqCost: p.record.moqCost,
|
||||
totalQtyAvail: p.record.totalQtyAvail,
|
||||
fees: {
|
||||
fbaFee: p.spApi.fbaFee,
|
||||
fbmFee: p.spApi.fbmFee,
|
||||
referralFeePercent: p.spApi.referralFeePercent,
|
||||
referralFee: Math.round(referralFee * 100) / 100,
|
||||
},
|
||||
sellerEligibility: {
|
||||
canSell: p.spApi.canSell,
|
||||
status: p.spApi.sellabilityStatus,
|
||||
reason: clampText(p.spApi.sellabilityReason, 120),
|
||||
},
|
||||
estimatedProfit: {
|
||||
fba: Math.round(fbaProfit * 100) / 100,
|
||||
fbm: Math.round(fbmProfit * 100) / 100,
|
||||
},
|
||||
estimatedROI: {
|
||||
fba:
|
||||
p.record.unitCost > 0
|
||||
? Math.round((fbaProfit / p.record.unitCost) * 100)
|
||||
: null,
|
||||
fbm:
|
||||
p.record.unitCost > 0
|
||||
? Math.round((fbmProfit / p.record.unitCost) * 100)
|
||||
: null,
|
||||
},
|
||||
};
|
||||
}
|
||||
|
||||
function clampText(value: unknown, maxLen: number): string | undefined {
|
||||
if (value == null) return undefined;
|
||||
const s = String(value).trim();
|
||||
if (!s) return undefined;
|
||||
return s.length > maxLen ? `${s.slice(0, maxLen - 1)}.` : s;
|
||||
}
|
||||
|
||||
function cleanLlmJson(text: string): string {
|
||||
// Remove ```json ... ``` or ``` ... ``` wrapping
|
||||
const fenceMatch = text.match(/```(?:json)?\s*\n?([\s\S]*?)```/);
|
||||
let cleaned = fenceMatch ? fenceMatch[1]!.trim() : text.trim();
|
||||
|
||||
// Strip any non-JSON wrapper text by taking the largest JSON-looking segment
|
||||
const firstArray = cleaned.indexOf("[");
|
||||
const firstObject = cleaned.indexOf("{");
|
||||
const startCandidates = [firstArray, firstObject].filter((i) => i >= 0);
|
||||
const start = startCandidates.length > 0 ? Math.min(...startCandidates) : -1;
|
||||
const endArray = cleaned.lastIndexOf("]");
|
||||
const endObject = cleaned.lastIndexOf("}");
|
||||
const end = Math.max(endArray, endObject);
|
||||
if (start >= 0 && end > start) {
|
||||
cleaned = cleaned.slice(start, end + 1);
|
||||
}
|
||||
|
||||
// Fix trailing comma-quote before closing brace: ,"} → "}
|
||||
cleaned = cleaned.replace(/,"\s*}/g, '"}');
|
||||
|
||||
// Fix malformed comma-quote before a closing bracket/brace: ,"} or ,"]
|
||||
cleaned = cleaned.replace(/,\s*"\s*([}\]])/g, "$1");
|
||||
|
||||
// Fix malformed quote-comma before a closing bracket/brace: ",} or ",]
|
||||
cleaned = cleaned.replace(/"\s*,\s*([}\]])/g, '"$1');
|
||||
|
||||
// Fix trailing commas before ] or }
|
||||
cleaned = cleaned.replace(/,\s*([}\]])/g, "$1");
|
||||
|
||||
return cleaned;
|
||||
}
|
||||
|
||||
function parseVerdicts(
|
||||
content: string,
|
||||
products: EnrichedProduct[],
|
||||
): LlmVerdict[] {
|
||||
const cleaned = cleanLlmJson(content);
|
||||
|
||||
try {
|
||||
const parsed = JSON.parse(cleaned) as unknown;
|
||||
return alignVerdicts(products, normalizeVerdicts(parsed));
|
||||
} catch (err) {
|
||||
const salvaged = extractVerdictsLoosely(cleaned);
|
||||
if (salvaged.length > 0) {
|
||||
console.warn(
|
||||
`LLM response was invalid JSON; salvaged ${salvaged.length} verdict(s) with loose parsing.`,
|
||||
);
|
||||
return alignVerdicts(products, salvaged);
|
||||
}
|
||||
|
||||
console.warn(
|
||||
"Failed to parse LLM response, marking all as ANALYSIS_FAILED",
|
||||
);
|
||||
console.warn("Raw LLM content:", content.slice(0, 500));
|
||||
return products.map((p) => ({
|
||||
asin: p.record.asin,
|
||||
verdict: "SKIP" as const,
|
||||
confidence: 0,
|
||||
reasoning: `Analysis failed: could not parse LLM output`,
|
||||
}));
|
||||
}
|
||||
}
|
||||
|
||||
function normalizeVerdicts(parsed: unknown): LlmVerdict[] {
|
||||
const container =
|
||||
parsed && typeof parsed === "object"
|
||||
? (parsed as Record<string, unknown>)
|
||||
: undefined;
|
||||
const nested = container?.verdicts ?? container?.results;
|
||||
|
||||
const arr: unknown[] = Array.isArray(parsed)
|
||||
? parsed
|
||||
: Array.isArray(nested)
|
||||
? nested
|
||||
: [parsed];
|
||||
|
||||
return arr
|
||||
.filter((v): v is Record<string, unknown> => !!v && typeof v === "object")
|
||||
.map((v) => ({
|
||||
asin: String(v.asin ?? "")
|
||||
.trim()
|
||||
.toUpperCase(),
|
||||
verdict: (String(v.verdict).toUpperCase() === "FBA" ||
|
||||
String(v.verdict).toUpperCase() === "FBM" ||
|
||||
String(v.verdict).toUpperCase() === "SKIP"
|
||||
? String(v.verdict).toUpperCase()
|
||||
: "SKIP") as LlmVerdict["verdict"],
|
||||
confidence: clampConfidence(
|
||||
typeof v.confidence === "number"
|
||||
? v.confidence
|
||||
: Number(v.confidence ?? 0),
|
||||
),
|
||||
reasoning: String(v.reasoning ?? "No reasoning provided"),
|
||||
}));
|
||||
}
|
||||
|
||||
function extractVerdictsLoosely(text: string): LlmVerdict[] {
|
||||
const objectMatches = text.match(/\{[\s\S]*?\}/g) ?? [];
|
||||
const verdicts: LlmVerdict[] = [];
|
||||
|
||||
for (const chunk of objectMatches) {
|
||||
const asin = extractField(chunk, /"asin"\s*:\s*"?([A-Z0-9]{10})"?/i) ?? "";
|
||||
const verdictRaw =
|
||||
extractField(chunk, /"verdict"\s*:\s*"?([A-Z]+)"?/i) ?? "SKIP";
|
||||
const confidenceRaw =
|
||||
extractField(chunk, /"confidence"\s*:\s*([0-9]+(?:\.[0-9]+)?)/i) ?? "0";
|
||||
const reasoning =
|
||||
extractField(chunk, /"reasoning"\s*:\s*"([\s\S]*?)"\s*(?:,|})/i) ??
|
||||
"No reasoning provided";
|
||||
|
||||
const normalizedVerdict = verdictRaw.toUpperCase();
|
||||
if (!asin) continue;
|
||||
|
||||
verdicts.push({
|
||||
asin,
|
||||
verdict: (normalizedVerdict === "FBA" ||
|
||||
normalizedVerdict === "FBM" ||
|
||||
normalizedVerdict === "SKIP"
|
||||
? normalizedVerdict
|
||||
: "SKIP") as LlmVerdict["verdict"],
|
||||
confidence: clampConfidence(Number(confidenceRaw)),
|
||||
reasoning,
|
||||
});
|
||||
}
|
||||
|
||||
return verdicts;
|
||||
}
|
||||
|
||||
function extractField(text: string, regex: RegExp): string | undefined {
|
||||
const match = text.match(regex);
|
||||
return match?.[1]?.trim();
|
||||
}
|
||||
|
||||
function clampConfidence(value: number): number {
|
||||
if (!Number.isFinite(value)) return 0;
|
||||
return Math.max(0, Math.min(100, Math.round(value)));
|
||||
}
|
||||
|
||||
function alignVerdicts(
|
||||
products: EnrichedProduct[],
|
||||
verdicts: LlmVerdict[],
|
||||
): LlmVerdict[] {
|
||||
const byAsin = new Map<string, LlmVerdict>();
|
||||
for (const verdict of verdicts) {
|
||||
if (verdict.asin && !byAsin.has(verdict.asin)) {
|
||||
byAsin.set(verdict.asin, verdict);
|
||||
}
|
||||
}
|
||||
|
||||
return products.map((product, index) => {
|
||||
const asin = product.record.asin;
|
||||
const byAsinVerdict = byAsin.get(asin);
|
||||
if (byAsinVerdict) return { ...byAsinVerdict, asin };
|
||||
|
||||
const byIndexVerdict = verdicts[index];
|
||||
if (byIndexVerdict) return { ...byIndexVerdict, asin };
|
||||
|
||||
return {
|
||||
asin,
|
||||
verdict: "SKIP" as const,
|
||||
confidence: 0,
|
||||
reasoning: "LLM returned no verdict for this product",
|
||||
};
|
||||
});
|
||||
}
|
||||
|
||||
418
src/reader.ts
418
src/reader.ts
@@ -1,209 +1,209 @@
|
||||
import * as XLSX from "xlsx";
|
||||
import type { ProductRecord } from "./types.ts";
|
||||
|
||||
const ASIN_REGEX = /^B[0-9A-Z]{9}$/;
|
||||
|
||||
const COLUMN_CANDIDATES = {
|
||||
asin: ["asin"],
|
||||
name: ["name", "product name", "title", "product title"],
|
||||
cost: ["unit cost", "cost", "unitcost", "unit_cost", "price", "buy cost"],
|
||||
brand: ["brand"],
|
||||
category: ["category"],
|
||||
amazonRank: ["amazon rank", "amazonrank", "sales rank", "bsr"],
|
||||
avgPrice90: [
|
||||
"90 day average",
|
||||
"90-day average",
|
||||
"avg price 90d",
|
||||
"avg 90 day",
|
||||
"90d average",
|
||||
],
|
||||
sellingPrice: ["selling price", "sale price", "sell price"],
|
||||
fbaNet: ["fba net", "fbanet", "fba_net"],
|
||||
grossProfit: ["gross profit $", "gross profit", "grossprofit"],
|
||||
grossProfitPct: ["gross profit %", "gross profit pct", "grossprofitpct"],
|
||||
netProfit: ["net profit", "netprofit"],
|
||||
roi: ["roi", "return on investment"],
|
||||
moq: ["moq", "min order qty", "minimum order quantity"],
|
||||
moqCost: ["moq cost", "moqcost", "moq_cost"],
|
||||
totalQty: ["total qty avail", "totalqtyavail", "qty available", "quantity"],
|
||||
link: ["link", "url", "source"],
|
||||
asinLink: ["asin link", "amazon link", "asin url"],
|
||||
sourceUrl: ["source url", "supplier url", "source link"],
|
||||
supplier: ["supplier", "vendor"],
|
||||
promoCouponCode: [
|
||||
"promo/coupon code",
|
||||
"promo coupon code",
|
||||
"coupon code",
|
||||
"promo code",
|
||||
],
|
||||
notes: ["notes", "note"],
|
||||
leadDate: ["date", "lead date"],
|
||||
} as const;
|
||||
|
||||
type ColumnKey = keyof typeof COLUMN_CANDIDATES;
|
||||
type ColumnMap = Record<ColumnKey, string | undefined>;
|
||||
|
||||
export function readProducts(filePath: string): ProductRecord[] {
|
||||
const workbook = XLSX.readFile(filePath);
|
||||
const sheetName = workbook.SheetNames[0];
|
||||
if (!sheetName) throw new Error("No sheets found in file");
|
||||
|
||||
const sheet = workbook.Sheets[sheetName]!;
|
||||
const rows = XLSX.utils.sheet_to_json<Record<string, unknown>>(sheet);
|
||||
|
||||
if (rows.length === 0) throw new Error("File contains no data rows");
|
||||
|
||||
const headers = Object.keys(rows[0]!);
|
||||
const columns = detectColumns(headers);
|
||||
const asinColumn = columns.asin;
|
||||
|
||||
if (!asinColumn)
|
||||
throw new Error(
|
||||
`No ASIN column found. Available columns: ${headers.join(", ")}`,
|
||||
);
|
||||
|
||||
logColumnDetection(headers, columns);
|
||||
|
||||
const knownCols = getKnownColumns(columns);
|
||||
|
||||
const products: ProductRecord[] = [];
|
||||
|
||||
for (const row of rows) {
|
||||
const asin = parseAsin(row[asinColumn]);
|
||||
if (!asin) continue;
|
||||
|
||||
const sourceUrl = getOptionalString(row, columns.sourceUrl);
|
||||
const asinLink = getOptionalString(row, columns.asinLink);
|
||||
const link = sourceUrl ?? asinLink ?? getOptionalString(row, columns.link);
|
||||
|
||||
const extra = getExtraFields(row, headers, knownCols);
|
||||
const netProfitFromSheet = getOptionalNumber(row, columns.netProfit);
|
||||
const roiFromSheet = getOptionalNumber(row, columns.roi);
|
||||
|
||||
products.push({
|
||||
asin,
|
||||
name: getOptionalString(row, columns.name) ?? "",
|
||||
unitCost: getOptionalNumber(row, columns.cost) ?? 0,
|
||||
brand: getOptionalString(row, columns.brand),
|
||||
category: getOptionalString(row, columns.category),
|
||||
amazonRank: getOptionalNumber(row, columns.amazonRank),
|
||||
avgPrice90FromSheet: getOptionalNumber(row, columns.avgPrice90),
|
||||
sellingPriceFromSheet: getOptionalNumber(row, columns.sellingPrice),
|
||||
fbaNet: getOptionalNumber(row, columns.fbaNet),
|
||||
grossProfit: getOptionalNumber(row, columns.grossProfit) ?? netProfitFromSheet,
|
||||
grossProfitPct:
|
||||
getOptionalNumber(row, columns.grossProfitPct) ?? roiFromSheet,
|
||||
netProfitFromSheet,
|
||||
roiFromSheet,
|
||||
moq: getOptionalNumber(row, columns.moq),
|
||||
moqCost: getOptionalNumber(row, columns.moqCost),
|
||||
totalQtyAvail: getOptionalNumber(row, columns.totalQty),
|
||||
link,
|
||||
asinLink,
|
||||
sourceUrl,
|
||||
supplier: getOptionalString(row, columns.supplier),
|
||||
promoCouponCode: getOptionalString(row, columns.promoCouponCode),
|
||||
notes: getOptionalString(row, columns.notes),
|
||||
leadDate: getOptionalString(row, columns.leadDate),
|
||||
...extra,
|
||||
});
|
||||
}
|
||||
|
||||
console.log(`Read ${products.length} valid products from ${filePath}`);
|
||||
return products;
|
||||
}
|
||||
|
||||
function detectColumns(headers: string[]): ColumnMap {
|
||||
const columns = {} as ColumnMap;
|
||||
for (const key of Object.keys(COLUMN_CANDIDATES) as ColumnKey[]) {
|
||||
columns[key] = findColumn(headers, [...COLUMN_CANDIDATES[key]]);
|
||||
}
|
||||
return columns;
|
||||
}
|
||||
|
||||
function logColumnDetection(headers: string[], columns: ColumnMap): void {
|
||||
console.log(`Found columns: ${headers.join(", ")}`);
|
||||
console.log(
|
||||
`Detected columns -> ASIN: ${columns.asin ?? "n/a"}, Name: ${columns.name ?? "n/a"}, Cost: ${columns.cost ?? "n/a"}, 90d Avg: ${columns.avgPrice90 ?? "n/a"}, Selling Price: ${columns.sellingPrice ?? "n/a"}, Net Profit: ${columns.netProfit ?? columns.grossProfit ?? "n/a"}, ROI: ${columns.roi ?? columns.grossProfitPct ?? "n/a"}, Source URL: ${columns.sourceUrl ?? "n/a"}, ASIN Link: ${columns.asinLink ?? "n/a"}`,
|
||||
);
|
||||
}
|
||||
|
||||
function getKnownColumns(columns: ColumnMap): Set<string> {
|
||||
return new Set(Object.values(columns).filter((column): column is string => !!column));
|
||||
}
|
||||
|
||||
function parseAsin(value: unknown): string | undefined {
|
||||
const asin = String(value ?? "")
|
||||
.trim()
|
||||
.toUpperCase();
|
||||
if (!asin || !ASIN_REGEX.test(asin)) {
|
||||
console.warn(`Skipping invalid ASIN: "${asin}"`);
|
||||
return undefined;
|
||||
}
|
||||
return asin;
|
||||
}
|
||||
|
||||
function getOptionalString(
|
||||
row: Record<string, unknown>,
|
||||
column: string | undefined,
|
||||
): string | undefined {
|
||||
if (!column) return undefined;
|
||||
return normalizeOptionalString(row[column]);
|
||||
}
|
||||
|
||||
function getOptionalNumber(
|
||||
row: Record<string, unknown>,
|
||||
column: string | undefined,
|
||||
): number | undefined {
|
||||
if (!column) return undefined;
|
||||
return parseOptionalNumber(row[column]);
|
||||
}
|
||||
|
||||
function getExtraFields(
|
||||
row: Record<string, unknown>,
|
||||
headers: string[],
|
||||
knownCols: Set<string>,
|
||||
): Record<string, unknown> {
|
||||
const extra: Record<string, unknown> = {};
|
||||
for (const header of headers) {
|
||||
if (!knownCols.has(header)) extra[header] = row[header];
|
||||
}
|
||||
return extra;
|
||||
}
|
||||
|
||||
function findColumn(
|
||||
headers: string[],
|
||||
candidates: string[],
|
||||
): string | undefined {
|
||||
const normalizedCandidates = new Set(candidates.map(normalizeHeader));
|
||||
|
||||
for (const header of headers) {
|
||||
if (normalizedCandidates.has(normalizeHeader(header))) {
|
||||
return header;
|
||||
}
|
||||
}
|
||||
|
||||
return undefined;
|
||||
}
|
||||
|
||||
function normalizeHeader(value: string): string {
|
||||
return value
|
||||
.toLowerCase()
|
||||
.trim()
|
||||
.replace(/%/g, " pct ")
|
||||
.replace(/\$/g, " usd ")
|
||||
.replace(/[^a-z0-9]/g, "");
|
||||
}
|
||||
|
||||
function normalizeOptionalString(value: unknown): string | undefined {
|
||||
if (value == null) return undefined;
|
||||
const s = String(value).trim();
|
||||
return s.length > 0 ? s : undefined;
|
||||
}
|
||||
|
||||
function parseOptionalNumber(value: unknown): number | undefined {
|
||||
if (value == null || value === "") return undefined;
|
||||
const cleaned = String(value).trim().replace(/[$,%]/g, "").replace(/,/g, "");
|
||||
const parsed = Number(cleaned);
|
||||
return Number.isFinite(parsed) ? parsed : undefined;
|
||||
}
|
||||
import * as XLSX from "xlsx";
|
||||
import type { ProductRecord } from "./types.ts";
|
||||
|
||||
const ASIN_REGEX = /^B[0-9A-Z]{9}$/;
|
||||
|
||||
const COLUMN_CANDIDATES = {
|
||||
asin: ["asin"],
|
||||
name: ["name", "product name", "title", "product title"],
|
||||
cost: ["unit cost", "cost", "unitcost", "unit_cost", "price", "buy cost"],
|
||||
brand: ["brand"],
|
||||
category: ["category"],
|
||||
amazonRank: ["amazon rank", "amazonrank", "sales rank", "bsr"],
|
||||
avgPrice90: [
|
||||
"90 day average",
|
||||
"90-day average",
|
||||
"avg price 90d",
|
||||
"avg 90 day",
|
||||
"90d average",
|
||||
],
|
||||
sellingPrice: ["selling price", "sale price", "sell price"],
|
||||
fbaNet: ["fba net", "fbanet", "fba_net"],
|
||||
grossProfit: ["gross profit $", "gross profit", "grossprofit"],
|
||||
grossProfitPct: ["gross profit %", "gross profit pct", "grossprofitpct"],
|
||||
netProfit: ["net profit", "netprofit"],
|
||||
roi: ["roi", "return on investment"],
|
||||
moq: ["moq", "min order qty", "minimum order quantity"],
|
||||
moqCost: ["moq cost", "moqcost", "moq_cost"],
|
||||
totalQty: ["total qty avail", "totalqtyavail", "qty available", "quantity"],
|
||||
link: ["link", "url", "source"],
|
||||
asinLink: ["asin link", "amazon link", "asin url"],
|
||||
sourceUrl: ["source url", "supplier url", "source link"],
|
||||
supplier: ["supplier", "vendor"],
|
||||
promoCouponCode: [
|
||||
"promo/coupon code",
|
||||
"promo coupon code",
|
||||
"coupon code",
|
||||
"promo code",
|
||||
],
|
||||
notes: ["notes", "note"],
|
||||
leadDate: ["date", "lead date"],
|
||||
} as const;
|
||||
|
||||
type ColumnKey = keyof typeof COLUMN_CANDIDATES;
|
||||
type ColumnMap = Record<ColumnKey, string | undefined>;
|
||||
|
||||
export function readProducts(filePath: string): ProductRecord[] {
|
||||
const workbook = XLSX.readFile(filePath);
|
||||
const sheetName = workbook.SheetNames[0];
|
||||
if (!sheetName) throw new Error("No sheets found in file");
|
||||
|
||||
const sheet = workbook.Sheets[sheetName]!;
|
||||
const rows = XLSX.utils.sheet_to_json<Record<string, unknown>>(sheet);
|
||||
|
||||
if (rows.length === 0) throw new Error("File contains no data rows");
|
||||
|
||||
const headers = Object.keys(rows[0]!);
|
||||
const columns = detectColumns(headers);
|
||||
const asinColumn = columns.asin;
|
||||
|
||||
if (!asinColumn)
|
||||
throw new Error(
|
||||
`No ASIN column found. Available columns: ${headers.join(", ")}`,
|
||||
);
|
||||
|
||||
logColumnDetection(headers, columns);
|
||||
|
||||
const knownCols = getKnownColumns(columns);
|
||||
|
||||
const products: ProductRecord[] = [];
|
||||
|
||||
for (const row of rows) {
|
||||
const asin = parseAsin(row[asinColumn]);
|
||||
if (!asin) continue;
|
||||
|
||||
const sourceUrl = getOptionalString(row, columns.sourceUrl);
|
||||
const asinLink = getOptionalString(row, columns.asinLink);
|
||||
const link = sourceUrl ?? asinLink ?? getOptionalString(row, columns.link);
|
||||
|
||||
const extra = getExtraFields(row, headers, knownCols);
|
||||
const netProfitFromSheet = getOptionalNumber(row, columns.netProfit);
|
||||
const roiFromSheet = getOptionalNumber(row, columns.roi);
|
||||
|
||||
products.push({
|
||||
asin,
|
||||
name: getOptionalString(row, columns.name) ?? "",
|
||||
unitCost: getOptionalNumber(row, columns.cost) ?? 0,
|
||||
brand: getOptionalString(row, columns.brand),
|
||||
category: getOptionalString(row, columns.category),
|
||||
amazonRank: getOptionalNumber(row, columns.amazonRank),
|
||||
avgPrice90FromSheet: getOptionalNumber(row, columns.avgPrice90),
|
||||
sellingPriceFromSheet: getOptionalNumber(row, columns.sellingPrice),
|
||||
fbaNet: getOptionalNumber(row, columns.fbaNet),
|
||||
grossProfit: getOptionalNumber(row, columns.grossProfit) ?? netProfitFromSheet,
|
||||
grossProfitPct:
|
||||
getOptionalNumber(row, columns.grossProfitPct) ?? roiFromSheet,
|
||||
netProfitFromSheet,
|
||||
roiFromSheet,
|
||||
moq: getOptionalNumber(row, columns.moq),
|
||||
moqCost: getOptionalNumber(row, columns.moqCost),
|
||||
totalQtyAvail: getOptionalNumber(row, columns.totalQty),
|
||||
link,
|
||||
asinLink,
|
||||
sourceUrl,
|
||||
supplier: getOptionalString(row, columns.supplier),
|
||||
promoCouponCode: getOptionalString(row, columns.promoCouponCode),
|
||||
notes: getOptionalString(row, columns.notes),
|
||||
leadDate: getOptionalString(row, columns.leadDate),
|
||||
...extra,
|
||||
});
|
||||
}
|
||||
|
||||
console.log(`Read ${products.length} valid products from ${filePath}`);
|
||||
return products;
|
||||
}
|
||||
|
||||
function detectColumns(headers: string[]): ColumnMap {
|
||||
const columns = {} as ColumnMap;
|
||||
for (const key of Object.keys(COLUMN_CANDIDATES) as ColumnKey[]) {
|
||||
columns[key] = findColumn(headers, [...COLUMN_CANDIDATES[key]]);
|
||||
}
|
||||
return columns;
|
||||
}
|
||||
|
||||
function logColumnDetection(headers: string[], columns: ColumnMap): void {
|
||||
console.log(`Found columns: ${headers.join(", ")}`);
|
||||
console.log(
|
||||
`Detected columns -> ASIN: ${columns.asin ?? "n/a"}, Name: ${columns.name ?? "n/a"}, Cost: ${columns.cost ?? "n/a"}, 90d Avg: ${columns.avgPrice90 ?? "n/a"}, Selling Price: ${columns.sellingPrice ?? "n/a"}, Net Profit: ${columns.netProfit ?? columns.grossProfit ?? "n/a"}, ROI: ${columns.roi ?? columns.grossProfitPct ?? "n/a"}, Source URL: ${columns.sourceUrl ?? "n/a"}, ASIN Link: ${columns.asinLink ?? "n/a"}`,
|
||||
);
|
||||
}
|
||||
|
||||
function getKnownColumns(columns: ColumnMap): Set<string> {
|
||||
return new Set(Object.values(columns).filter((column): column is string => !!column));
|
||||
}
|
||||
|
||||
function parseAsin(value: unknown): string | undefined {
|
||||
const asin = String(value ?? "")
|
||||
.trim()
|
||||
.toUpperCase();
|
||||
if (!asin || !ASIN_REGEX.test(asin)) {
|
||||
console.warn(`Skipping invalid ASIN: "${asin}"`);
|
||||
return undefined;
|
||||
}
|
||||
return asin;
|
||||
}
|
||||
|
||||
function getOptionalString(
|
||||
row: Record<string, unknown>,
|
||||
column: string | undefined,
|
||||
): string | undefined {
|
||||
if (!column) return undefined;
|
||||
return normalizeOptionalString(row[column]);
|
||||
}
|
||||
|
||||
function getOptionalNumber(
|
||||
row: Record<string, unknown>,
|
||||
column: string | undefined,
|
||||
): number | undefined {
|
||||
if (!column) return undefined;
|
||||
return parseOptionalNumber(row[column]);
|
||||
}
|
||||
|
||||
function getExtraFields(
|
||||
row: Record<string, unknown>,
|
||||
headers: string[],
|
||||
knownCols: Set<string>,
|
||||
): Record<string, unknown> {
|
||||
const extra: Record<string, unknown> = {};
|
||||
for (const header of headers) {
|
||||
if (!knownCols.has(header)) extra[header] = row[header];
|
||||
}
|
||||
return extra;
|
||||
}
|
||||
|
||||
function findColumn(
|
||||
headers: string[],
|
||||
candidates: string[],
|
||||
): string | undefined {
|
||||
const normalizedCandidates = new Set(candidates.map(normalizeHeader));
|
||||
|
||||
for (const header of headers) {
|
||||
if (normalizedCandidates.has(normalizeHeader(header))) {
|
||||
return header;
|
||||
}
|
||||
}
|
||||
|
||||
return undefined;
|
||||
}
|
||||
|
||||
function normalizeHeader(value: string): string {
|
||||
return value
|
||||
.toLowerCase()
|
||||
.trim()
|
||||
.replace(/%/g, " pct ")
|
||||
.replace(/\$/g, " usd ")
|
||||
.replace(/[^a-z0-9]/g, "");
|
||||
}
|
||||
|
||||
function normalizeOptionalString(value: unknown): string | undefined {
|
||||
if (value == null) return undefined;
|
||||
const s = String(value).trim();
|
||||
return s.length > 0 ? s : undefined;
|
||||
}
|
||||
|
||||
function parseOptionalNumber(value: unknown): number | undefined {
|
||||
if (value == null || value === "") return undefined;
|
||||
const cleaned = String(value).trim().replace(/[$,%]/g, "").replace(/,/g, "");
|
||||
const parsed = Number(cleaned);
|
||||
return Number.isFinite(parsed) ? parsed : undefined;
|
||||
}
|
||||
|
||||
1300
src/sp-api.ts
1300
src/sp-api.ts
File diff suppressed because it is too large
Load Diff
@@ -1,48 +1,48 @@
|
||||
import { testSpApiConnectivity, testSpApiSellability } from "./sp-api.ts";
|
||||
|
||||
function parseArgs(): { asin?: string; sellabilityMode: boolean } {
|
||||
const args = process.argv.slice(2);
|
||||
const sellabilityMode = args.includes("--sellability");
|
||||
const asin = args.find((arg) => !arg.startsWith("--"));
|
||||
return { asin, sellabilityMode };
|
||||
}
|
||||
|
||||
async function main() {
|
||||
const { asin, sellabilityMode } = parseArgs();
|
||||
|
||||
console.log("Running SP-API connectivity test...");
|
||||
|
||||
if (sellabilityMode) {
|
||||
if (!asin) {
|
||||
console.error("Usage: bun run src/sp-test.ts --sellability <ASIN>");
|
||||
process.exit(1);
|
||||
}
|
||||
|
||||
console.log(`Running sellability check for ASIN: ${asin}`);
|
||||
const sellability = await testSpApiSellability(asin);
|
||||
if (!sellability.ok) {
|
||||
console.error(`SP-API sellability test failed: ${sellability.message}`);
|
||||
process.exit(1);
|
||||
}
|
||||
|
||||
console.log(`SP-API sellability test passed: ${sellability.message}`);
|
||||
return;
|
||||
}
|
||||
|
||||
if (asin) {
|
||||
console.log(`Including pricing connectivity check for ASIN: ${asin}`);
|
||||
}
|
||||
|
||||
const result = await testSpApiConnectivity(asin);
|
||||
if (!result.ok) {
|
||||
console.error(`SP-API test failed: ${result.message}`);
|
||||
process.exit(1);
|
||||
}
|
||||
|
||||
console.log(`SP-API test passed: ${result.message}`);
|
||||
}
|
||||
|
||||
main().catch((err) => {
|
||||
console.error(`SP-API test crashed: ${String(err)}`);
|
||||
process.exit(1);
|
||||
});
|
||||
import { testSpApiConnectivity, testSpApiSellability } from "./sp-api.ts";
|
||||
|
||||
function parseArgs(): { asin?: string; sellabilityMode: boolean } {
|
||||
const args = process.argv.slice(2);
|
||||
const sellabilityMode = args.includes("--sellability");
|
||||
const asin = args.find((arg) => !arg.startsWith("--"));
|
||||
return { asin, sellabilityMode };
|
||||
}
|
||||
|
||||
async function main() {
|
||||
const { asin, sellabilityMode } = parseArgs();
|
||||
|
||||
console.log("Running SP-API connectivity test...");
|
||||
|
||||
if (sellabilityMode) {
|
||||
if (!asin) {
|
||||
console.error("Usage: bun run src/sp-test.ts --sellability <ASIN>");
|
||||
process.exit(1);
|
||||
}
|
||||
|
||||
console.log(`Running sellability check for ASIN: ${asin}`);
|
||||
const sellability = await testSpApiSellability(asin);
|
||||
if (!sellability.ok) {
|
||||
console.error(`SP-API sellability test failed: ${sellability.message}`);
|
||||
process.exit(1);
|
||||
}
|
||||
|
||||
console.log(`SP-API sellability test passed: ${sellability.message}`);
|
||||
return;
|
||||
}
|
||||
|
||||
if (asin) {
|
||||
console.log(`Including pricing connectivity check for ASIN: ${asin}`);
|
||||
}
|
||||
|
||||
const result = await testSpApiConnectivity(asin);
|
||||
if (!result.ok) {
|
||||
console.error(`SP-API test failed: ${result.message}`);
|
||||
process.exit(1);
|
||||
}
|
||||
|
||||
console.log(`SP-API test passed: ${result.message}`);
|
||||
}
|
||||
|
||||
main().catch((err) => {
|
||||
console.error(`SP-API test crashed: ${String(err)}`);
|
||||
process.exit(1);
|
||||
});
|
||||
|
||||
150
src/types.ts
150
src/types.ts
@@ -1,75 +1,75 @@
|
||||
export interface ProductRecord {
|
||||
asin: string;
|
||||
name: string;
|
||||
unitCost: number;
|
||||
brand?: string;
|
||||
category?: string;
|
||||
amazonRank?: number;
|
||||
avgPrice90FromSheet?: number;
|
||||
sellingPriceFromSheet?: number;
|
||||
fbaNet?: number;
|
||||
grossProfit?: number;
|
||||
grossProfitPct?: number;
|
||||
netProfitFromSheet?: number;
|
||||
roiFromSheet?: number;
|
||||
moq?: number;
|
||||
moqCost?: number;
|
||||
totalQtyAvail?: number;
|
||||
|
||||
link?: string;
|
||||
asinLink?: string;
|
||||
sourceUrl?: string;
|
||||
supplier?: string;
|
||||
promoCouponCode?: string;
|
||||
notes?: string;
|
||||
leadDate?: string;
|
||||
[key: string]: unknown;
|
||||
}
|
||||
|
||||
export interface KeepaData {
|
||||
currentPrice: number | null;
|
||||
avgPrice90: number | null;
|
||||
minPrice90: number | null;
|
||||
maxPrice90: number | null;
|
||||
salesRank: number | null;
|
||||
salesRankAvg90: number | null;
|
||||
salesRankDrops30: number | null;
|
||||
salesRankDrops90: number | null;
|
||||
sellerCount: number | null;
|
||||
buyBoxSeller: string | null;
|
||||
buyBoxPrice: number | null;
|
||||
monthlySold: number | null;
|
||||
categoryTree: string[];
|
||||
}
|
||||
|
||||
export type SellabilityInfo = {
|
||||
canSell: boolean | null;
|
||||
sellabilityStatus: "available" | "restricted" | "not_available" | "unknown";
|
||||
sellabilityReason?: string;
|
||||
};
|
||||
|
||||
export interface SpApiData extends SellabilityInfo {
|
||||
fbaFee: number;
|
||||
fbmFee: number;
|
||||
referralFeePercent: number;
|
||||
estimatedSalePrice: number;
|
||||
}
|
||||
|
||||
export interface EnrichedProduct {
|
||||
record: ProductRecord;
|
||||
keepa: KeepaData | null;
|
||||
spApi: SpApiData;
|
||||
fetchedAt: string;
|
||||
}
|
||||
|
||||
export interface LlmVerdict {
|
||||
asin: string;
|
||||
verdict: "FBA" | "FBM" | "SKIP";
|
||||
confidence: number;
|
||||
reasoning: string;
|
||||
}
|
||||
|
||||
export interface AnalysisResult {
|
||||
product: EnrichedProduct;
|
||||
verdict: LlmVerdict;
|
||||
}
|
||||
export interface ProductRecord {
|
||||
asin: string;
|
||||
name: string;
|
||||
unitCost: number;
|
||||
brand?: string;
|
||||
category?: string;
|
||||
amazonRank?: number;
|
||||
avgPrice90FromSheet?: number;
|
||||
sellingPriceFromSheet?: number;
|
||||
fbaNet?: number;
|
||||
grossProfit?: number;
|
||||
grossProfitPct?: number;
|
||||
netProfitFromSheet?: number;
|
||||
roiFromSheet?: number;
|
||||
moq?: number;
|
||||
moqCost?: number;
|
||||
totalQtyAvail?: number;
|
||||
|
||||
link?: string;
|
||||
asinLink?: string;
|
||||
sourceUrl?: string;
|
||||
supplier?: string;
|
||||
promoCouponCode?: string;
|
||||
notes?: string;
|
||||
leadDate?: string;
|
||||
[key: string]: unknown;
|
||||
}
|
||||
|
||||
export interface KeepaData {
|
||||
currentPrice: number | null;
|
||||
avgPrice90: number | null;
|
||||
minPrice90: number | null;
|
||||
maxPrice90: number | null;
|
||||
salesRank: number | null;
|
||||
salesRankAvg90: number | null;
|
||||
salesRankDrops30: number | null;
|
||||
salesRankDrops90: number | null;
|
||||
sellerCount: number | null;
|
||||
buyBoxSeller: string | null;
|
||||
buyBoxPrice: number | null;
|
||||
monthlySold: number | null;
|
||||
categoryTree: string[];
|
||||
}
|
||||
|
||||
export type SellabilityInfo = {
|
||||
canSell: boolean | null;
|
||||
sellabilityStatus: "available" | "restricted" | "not_available" | "unknown";
|
||||
sellabilityReason?: string;
|
||||
};
|
||||
|
||||
export interface SpApiData extends SellabilityInfo {
|
||||
fbaFee: number;
|
||||
fbmFee: number;
|
||||
referralFeePercent: number;
|
||||
estimatedSalePrice: number;
|
||||
}
|
||||
|
||||
export interface EnrichedProduct {
|
||||
record: ProductRecord;
|
||||
keepa: KeepaData | null;
|
||||
spApi: SpApiData;
|
||||
fetchedAt: string;
|
||||
}
|
||||
|
||||
export interface LlmVerdict {
|
||||
asin: string;
|
||||
verdict: "FBA" | "FBM" | "SKIP";
|
||||
confidence: number;
|
||||
reasoning: string;
|
||||
}
|
||||
|
||||
export interface AnalysisResult {
|
||||
product: EnrichedProduct;
|
||||
verdict: LlmVerdict;
|
||||
}
|
||||
|
||||
318
src/writer.ts
318
src/writer.ts
@@ -1,159 +1,159 @@
|
||||
import * as XLSX from "xlsx";
|
||||
import type { AnalysisResult } from "./types.ts";
|
||||
|
||||
function buildRow(r: AnalysisResult) {
|
||||
const price =
|
||||
r.product.keepa?.currentPrice ??
|
||||
r.product.record.sellingPriceFromSheet ??
|
||||
r.product.spApi.estimatedSalePrice;
|
||||
const rank = r.product.keepa?.salesRank ?? r.product.record.amazonRank;
|
||||
|
||||
return {
|
||||
ASIN: r.product.record.asin,
|
||||
Name: r.product.record.name,
|
||||
Brand: r.product.record.brand ?? "",
|
||||
Category:
|
||||
r.product.record.category ??
|
||||
r.product.keepa?.categoryTree?.join(" > ") ??
|
||||
"",
|
||||
"Unit Cost": r.product.record.unitCost,
|
||||
"Current Price": price ?? "",
|
||||
"Avg Price 90d": r.product.keepa?.avgPrice90 ?? "",
|
||||
"Avg Price 90d (sheet)": r.product.record.avgPrice90FromSheet ?? "",
|
||||
"Selling Price (sheet)": r.product.record.sellingPriceFromSheet ?? "",
|
||||
"Sales Rank": rank ?? "",
|
||||
"Rank Avg 90d": r.product.keepa?.salesRankAvg90 ?? "",
|
||||
Sellers: r.product.keepa?.sellerCount ?? "",
|
||||
"Monthly Sold": r.product.keepa?.monthlySold ?? "",
|
||||
"Rank Drops 30d": r.product.keepa?.salesRankDrops30 ?? "",
|
||||
"Rank Drops 90d": r.product.keepa?.salesRankDrops90 ?? "",
|
||||
"FBA Net (sheet)": r.product.record.fbaNet ?? "",
|
||||
"Gross Profit $": r.product.record.grossProfit ?? "",
|
||||
"Gross Profit %": r.product.record.grossProfitPct ?? "",
|
||||
"Net Profit (sheet)": r.product.record.netProfitFromSheet ?? "",
|
||||
"ROI (sheet)": r.product.record.roiFromSheet ?? "",
|
||||
MOQ: r.product.record.moq ?? "",
|
||||
"MOQ Cost": r.product.record.moqCost ?? "",
|
||||
"Qty Available": r.product.record.totalQtyAvail ?? "",
|
||||
Supplier: r.product.record.supplier ?? "",
|
||||
"Source URL": r.product.record.sourceUrl ?? "",
|
||||
"ASIN Link": r.product.record.asinLink ?? "",
|
||||
"Promo/Coupon Code": r.product.record.promoCouponCode ?? "",
|
||||
Notes: r.product.record.notes ?? "",
|
||||
"Lead Date": r.product.record.leadDate ?? "",
|
||||
"FBA Fee": r.product.spApi.fbaFee,
|
||||
"FBM Fee": r.product.spApi.fbmFee,
|
||||
"Referral %": r.product.spApi.referralFeePercent,
|
||||
"Can Sell":
|
||||
r.product.spApi.canSell == null
|
||||
? "unknown"
|
||||
: r.product.spApi.canSell
|
||||
? "yes"
|
||||
: "no",
|
||||
Sellability: r.product.spApi.sellabilityStatus,
|
||||
"Sellability Reason": r.product.spApi.sellabilityReason ?? "",
|
||||
Verdict: r.verdict.verdict,
|
||||
Confidence: r.verdict.confidence,
|
||||
Reasoning: r.verdict.reasoning,
|
||||
};
|
||||
}
|
||||
|
||||
export function printResults(results: AnalysisResult[]): void {
|
||||
const rows = results
|
||||
.filter((r) => r.verdict.verdict === "FBA" || r.verdict.verdict === "FBM")
|
||||
.map((r) => {
|
||||
const sellingPrice =
|
||||
r.product.keepa?.currentPrice ??
|
||||
r.product.record.sellingPriceFromSheet ??
|
||||
r.product.spApi.estimatedSalePrice;
|
||||
const referralFee =
|
||||
sellingPrice != null
|
||||
? sellingPrice * (r.product.spApi.referralFeePercent / 100)
|
||||
: null;
|
||||
const fulfillmentFee =
|
||||
r.verdict.verdict === "FBA"
|
||||
? r.product.spApi.fbaFee
|
||||
: r.product.spApi.fbmFee;
|
||||
const netProfit =
|
||||
sellingPrice != null
|
||||
? Math.round(
|
||||
(sellingPrice -
|
||||
r.product.record.unitCost -
|
||||
fulfillmentFee -
|
||||
(referralFee ?? 0)) *
|
||||
100,
|
||||
) / 100
|
||||
: "";
|
||||
|
||||
return {
|
||||
ASIN: r.product.record.asin,
|
||||
Name: r.product.record.name.slice(0, 40),
|
||||
Category: String(
|
||||
r.product.record.category ??
|
||||
r.product.keepa?.categoryTree?.join(" > ") ??
|
||||
"",
|
||||
).slice(0, 20),
|
||||
"Unit Cost": r.product.record.unitCost,
|
||||
"Selling Price": sellingPrice ?? "",
|
||||
"Net Profit": netProfit,
|
||||
"Monthly Sold": r.product.keepa?.monthlySold ?? "",
|
||||
"Sold 90 Day": r.product.keepa?.salesRankDrops90 ?? "",
|
||||
"Can Sell":
|
||||
r.product.spApi.canSell == null
|
||||
? "unknown"
|
||||
: r.product.spApi.canSell
|
||||
? "yes"
|
||||
: "no",
|
||||
Sellability: r.product.spApi.sellabilityStatus,
|
||||
"Sellability Reason": String(
|
||||
r.product.spApi.sellabilityReason ?? "",
|
||||
).slice(0, 60),
|
||||
Confidence: r.verdict.confidence,
|
||||
Reasoning: r.verdict.reasoning.slice(0, 60),
|
||||
};
|
||||
});
|
||||
|
||||
console.log("\n=== Analysis Results ===\n");
|
||||
if (rows.length === 0) {
|
||||
console.log("No FBA/FBM leads found.");
|
||||
} else {
|
||||
console.table(rows);
|
||||
}
|
||||
|
||||
const summary = {
|
||||
FBA: results.filter((r) => r.verdict.verdict === "FBA").length,
|
||||
FBM: results.filter((r) => r.verdict.verdict === "FBM").length,
|
||||
SKIP: results.filter((r) => r.verdict.verdict === "SKIP").length,
|
||||
Available: results.filter(
|
||||
(r) => r.product.spApi.sellabilityStatus === "available",
|
||||
).length,
|
||||
Restricted: results.filter(
|
||||
(r) => r.product.spApi.sellabilityStatus === "restricted",
|
||||
).length,
|
||||
NotAvailable: results.filter(
|
||||
(r) => r.product.spApi.sellabilityStatus === "not_available",
|
||||
).length,
|
||||
Unknown: results.filter(
|
||||
(r) => r.product.spApi.sellabilityStatus === "unknown",
|
||||
).length,
|
||||
};
|
||||
console.log(
|
||||
`\nSummary: ${summary.FBA} FBA | ${summary.FBM} FBM | ${summary.SKIP} SKIP out of ${results.length} products\n`,
|
||||
);
|
||||
console.log(
|
||||
`Sellability: ${summary.Available} available | ${summary.Restricted} restricted | ${summary.NotAvailable} not_available | ${summary.Unknown} unknown\n`,
|
||||
);
|
||||
}
|
||||
|
||||
export function writeResultsCsv(
|
||||
results: AnalysisResult[],
|
||||
outputPath: string,
|
||||
): void {
|
||||
const rows = results.map(buildRow);
|
||||
|
||||
const ws = XLSX.utils.json_to_sheet(rows);
|
||||
const wb = XLSX.utils.book_new();
|
||||
XLSX.utils.book_append_sheet(wb, ws, "Results");
|
||||
XLSX.writeFile(wb, outputPath);
|
||||
console.log(`Results written to ${outputPath}`);
|
||||
}
|
||||
import * as XLSX from "xlsx";
|
||||
import type { AnalysisResult } from "./types.ts";
|
||||
|
||||
function buildRow(r: AnalysisResult) {
|
||||
const price =
|
||||
r.product.keepa?.currentPrice ??
|
||||
r.product.record.sellingPriceFromSheet ??
|
||||
r.product.spApi.estimatedSalePrice;
|
||||
const rank = r.product.keepa?.salesRank ?? r.product.record.amazonRank;
|
||||
|
||||
return {
|
||||
ASIN: r.product.record.asin,
|
||||
Name: r.product.record.name,
|
||||
Brand: r.product.record.brand ?? "",
|
||||
Category:
|
||||
r.product.record.category ??
|
||||
r.product.keepa?.categoryTree?.join(" > ") ??
|
||||
"",
|
||||
"Unit Cost": r.product.record.unitCost,
|
||||
"Current Price": price ?? "",
|
||||
"Avg Price 90d": r.product.keepa?.avgPrice90 ?? "",
|
||||
"Avg Price 90d (sheet)": r.product.record.avgPrice90FromSheet ?? "",
|
||||
"Selling Price (sheet)": r.product.record.sellingPriceFromSheet ?? "",
|
||||
"Sales Rank": rank ?? "",
|
||||
"Rank Avg 90d": r.product.keepa?.salesRankAvg90 ?? "",
|
||||
Sellers: r.product.keepa?.sellerCount ?? "",
|
||||
"Monthly Sold": r.product.keepa?.monthlySold ?? "",
|
||||
"Rank Drops 30d": r.product.keepa?.salesRankDrops30 ?? "",
|
||||
"Rank Drops 90d": r.product.keepa?.salesRankDrops90 ?? "",
|
||||
"FBA Net (sheet)": r.product.record.fbaNet ?? "",
|
||||
"Gross Profit $": r.product.record.grossProfit ?? "",
|
||||
"Gross Profit %": r.product.record.grossProfitPct ?? "",
|
||||
"Net Profit (sheet)": r.product.record.netProfitFromSheet ?? "",
|
||||
"ROI (sheet)": r.product.record.roiFromSheet ?? "",
|
||||
MOQ: r.product.record.moq ?? "",
|
||||
"MOQ Cost": r.product.record.moqCost ?? "",
|
||||
"Qty Available": r.product.record.totalQtyAvail ?? "",
|
||||
Supplier: r.product.record.supplier ?? "",
|
||||
"Source URL": r.product.record.sourceUrl ?? "",
|
||||
"ASIN Link": r.product.record.asinLink ?? "",
|
||||
"Promo/Coupon Code": r.product.record.promoCouponCode ?? "",
|
||||
Notes: r.product.record.notes ?? "",
|
||||
"Lead Date": r.product.record.leadDate ?? "",
|
||||
"FBA Fee": r.product.spApi.fbaFee,
|
||||
"FBM Fee": r.product.spApi.fbmFee,
|
||||
"Referral %": r.product.spApi.referralFeePercent,
|
||||
"Can Sell":
|
||||
r.product.spApi.canSell == null
|
||||
? "unknown"
|
||||
: r.product.spApi.canSell
|
||||
? "yes"
|
||||
: "no",
|
||||
Sellability: r.product.spApi.sellabilityStatus,
|
||||
"Sellability Reason": r.product.spApi.sellabilityReason ?? "",
|
||||
Verdict: r.verdict.verdict,
|
||||
Confidence: r.verdict.confidence,
|
||||
Reasoning: r.verdict.reasoning,
|
||||
};
|
||||
}
|
||||
|
||||
export function printResults(results: AnalysisResult[]): void {
|
||||
const rows = results
|
||||
.filter((r) => r.verdict.verdict === "FBA" || r.verdict.verdict === "FBM")
|
||||
.map((r) => {
|
||||
const sellingPrice =
|
||||
r.product.keepa?.currentPrice ??
|
||||
r.product.record.sellingPriceFromSheet ??
|
||||
r.product.spApi.estimatedSalePrice;
|
||||
const referralFee =
|
||||
sellingPrice != null
|
||||
? sellingPrice * (r.product.spApi.referralFeePercent / 100)
|
||||
: null;
|
||||
const fulfillmentFee =
|
||||
r.verdict.verdict === "FBA"
|
||||
? r.product.spApi.fbaFee
|
||||
: r.product.spApi.fbmFee;
|
||||
const netProfit =
|
||||
sellingPrice != null
|
||||
? Math.round(
|
||||
(sellingPrice -
|
||||
r.product.record.unitCost -
|
||||
fulfillmentFee -
|
||||
(referralFee ?? 0)) *
|
||||
100,
|
||||
) / 100
|
||||
: "";
|
||||
|
||||
return {
|
||||
ASIN: r.product.record.asin,
|
||||
Name: r.product.record.name.slice(0, 40),
|
||||
Category: String(
|
||||
r.product.record.category ??
|
||||
r.product.keepa?.categoryTree?.join(" > ") ??
|
||||
"",
|
||||
).slice(0, 20),
|
||||
"Unit Cost": r.product.record.unitCost,
|
||||
"Selling Price": sellingPrice ?? "",
|
||||
"Net Profit": netProfit,
|
||||
"Monthly Sold": r.product.keepa?.monthlySold ?? "",
|
||||
"Sold 90 Day": r.product.keepa?.salesRankDrops90 ?? "",
|
||||
"Can Sell":
|
||||
r.product.spApi.canSell == null
|
||||
? "unknown"
|
||||
: r.product.spApi.canSell
|
||||
? "yes"
|
||||
: "no",
|
||||
Sellability: r.product.spApi.sellabilityStatus,
|
||||
"Sellability Reason": String(
|
||||
r.product.spApi.sellabilityReason ?? "",
|
||||
).slice(0, 60),
|
||||
Confidence: r.verdict.confidence,
|
||||
Reasoning: r.verdict.reasoning.slice(0, 60),
|
||||
};
|
||||
});
|
||||
|
||||
console.log("\n=== Analysis Results ===\n");
|
||||
if (rows.length === 0) {
|
||||
console.log("No FBA/FBM leads found.");
|
||||
} else {
|
||||
console.table(rows);
|
||||
}
|
||||
|
||||
const summary = {
|
||||
FBA: results.filter((r) => r.verdict.verdict === "FBA").length,
|
||||
FBM: results.filter((r) => r.verdict.verdict === "FBM").length,
|
||||
SKIP: results.filter((r) => r.verdict.verdict === "SKIP").length,
|
||||
Available: results.filter(
|
||||
(r) => r.product.spApi.sellabilityStatus === "available",
|
||||
).length,
|
||||
Restricted: results.filter(
|
||||
(r) => r.product.spApi.sellabilityStatus === "restricted",
|
||||
).length,
|
||||
NotAvailable: results.filter(
|
||||
(r) => r.product.spApi.sellabilityStatus === "not_available",
|
||||
).length,
|
||||
Unknown: results.filter(
|
||||
(r) => r.product.spApi.sellabilityStatus === "unknown",
|
||||
).length,
|
||||
};
|
||||
console.log(
|
||||
`\nSummary: ${summary.FBA} FBA | ${summary.FBM} FBM | ${summary.SKIP} SKIP out of ${results.length} products\n`,
|
||||
);
|
||||
console.log(
|
||||
`Sellability: ${summary.Available} available | ${summary.Restricted} restricted | ${summary.NotAvailable} not_available | ${summary.Unknown} unknown\n`,
|
||||
);
|
||||
}
|
||||
|
||||
export function writeResultsCsv(
|
||||
results: AnalysisResult[],
|
||||
outputPath: string,
|
||||
): void {
|
||||
const rows = results.map(buildRow);
|
||||
|
||||
const ws = XLSX.utils.json_to_sheet(rows);
|
||||
const wb = XLSX.utils.book_new();
|
||||
XLSX.utils.book_append_sheet(wb, ws, "Results");
|
||||
XLSX.writeFile(wb, outputPath);
|
||||
console.log(`Results written to ${outputPath}`);
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user