fix(storefront-chat): ground AI replies in catalog and stop KB noise
- Filter stopwords from retrieval term matching so generic words do not score unrelated KB chunks. - For product-availability questions with no product or KB hits, return a deterministic cannot-confirm reply (skip LLM). - Tighten system prompt: no invented inventory, menus, or URLs; lower temperature. Made-with: Cursor
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talatops
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aa871ff942
@ -7,6 +7,16 @@ type HistoryMessage = {
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content: string
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}
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/** Customer is asking whether the store carries / sells a product (not policy/shipping). */
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function isAskingAboutProductAvailability(query: string) {
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return /\b(do you have|have any|have you got|carry|carrying|sell|selling|in stock|out of stock|stock|available|got any|do you sell|do you carry|looking for|can i (get|buy)|can you get)\b/i.test(
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query.trim()
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)
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}
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const NO_EVIDENCE_PRODUCT_REPLY =
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"I do not see that item in this store’s catalog or FAQs I have access to, so I can’t confirm we carry it. If you have another product name or category from this shop, I can check again."
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export async function generateStorefrontReply(params: {
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storeId: string
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query: string
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@ -17,6 +27,34 @@ export async function generateStorefrontReply(params: {
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const { storeId, query, visitorId, history } = params
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const retrieval = await getBlendedStorefrontContext({ storeId, query })
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// Hard guard: do not invent inventory. If they ask “do you have X?” and we have no product row and no KB/FAQ hit, answer without the LLM.
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if (
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isAskingAboutProductAvailability(query) &&
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retrieval.productCount === 0 &&
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retrieval.kbCount === 0
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) {
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logger.info("[STOREFRONT_AI_REPLY]", {
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storeId,
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visitorId,
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queryLength: query.length,
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kbHits: retrieval.kbCount,
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productHits: retrieval.productCount,
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latencyMs: Date.now() - startedAt,
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fallbackUsed: true,
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groundedSkipLlm: true,
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error: null,
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})
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return {
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content: NO_EVIDENCE_PRODUCT_REPLY,
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meta: {
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kbHits: retrieval.kbCount,
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productHits: retrieval.productCount,
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fallbackUsed: true,
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},
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}
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}
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const contextLines = retrieval.items.map(
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(item, idx) => `[${idx + 1}] (${item.source}) ${item.title}: ${item.content}`
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)
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@ -30,12 +68,13 @@ export async function generateStorefrontReply(params: {
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})) as GroqChatMessage[]
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const system = [
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"You are JUNO storefront assistant for an ecommerce store.",
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"Use the provided context first (products, FAQs, knowledge).",
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"If context is insufficient, ask one concise clarifying question.",
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"Do not invent exact prices, stock or policy details that are not present.",
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"Keep responses concise, friendly, and sales-supportive.",
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"Return plain text only.",
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"You are the JUNO storefront assistant. You ONLY answer using the Context block below (products, FAQs, knowledge chunks).",
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"If the Context does not clearly support an answer, say you cannot find it in the catalog or docs you have—do NOT guess.",
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"Never claim a product exists, is in stock, or that the store carries a category unless a Context line explicitly supports it.",
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"Never invent website layout: no tabs, menus, dropdowns, or navigation paths unless they appear verbatim in Context.",
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"Never invent URLs or deep links unless they appear in Context.",
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"Do not affirm availability with “yes” unless a PRODUCT line or FAQ/KB line in Context clearly covers what the customer asked.",
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"Be concise and friendly. Plain text only.",
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].join(" ")
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const user = [
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@ -53,13 +92,13 @@ export async function generateStorefrontReply(params: {
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]
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const out = await groqChatCompletion(messages, {
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temperature: 0.2,
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temperature: 0.1,
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maxTokens: 420,
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timeoutMs: 28_000,
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})
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const fallback =
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"Thanks for your message. I do not have enough details right now. Could you share the product name or what exactly you want to know?"
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"I don’t have enough in the store’s catalog or FAQ context to answer that accurately. What product name or topic from this shop should I look for?"
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const content = (out.content || "").trim() || fallback
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@ -7,12 +7,128 @@ type RetrievedContextItem = {
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score: number
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}
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/** Strip generic words so "do you have socks?" does not match random KB via "you"/"do". */
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const STOPWORDS = new Set([
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"the",
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"a",
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"an",
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"and",
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"or",
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"but",
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"in",
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"on",
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"at",
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"to",
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"for",
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"of",
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"as",
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"by",
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"with",
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"from",
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"is",
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"are",
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"was",
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"were",
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"be",
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"been",
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"being",
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"have",
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"has",
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"had",
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"do",
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"does",
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"did",
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"will",
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"would",
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"could",
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"should",
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"may",
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"might",
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"must",
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"can",
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"this",
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"that",
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"these",
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"those",
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"i",
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"me",
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"my",
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"you",
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"your",
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"it",
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"its",
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"we",
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"our",
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"they",
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"them",
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"their",
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"what",
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"which",
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"who",
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"whom",
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"whose",
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"where",
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"when",
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"why",
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"how",
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"all",
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"each",
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"every",
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"both",
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"few",
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"more",
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"most",
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"other",
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"some",
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"such",
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"no",
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"nor",
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"not",
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"only",
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"own",
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"same",
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"so",
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"than",
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"too",
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"very",
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"just",
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"any",
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"there",
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"here",
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"about",
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"into",
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"through",
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"during",
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"before",
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"after",
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"above",
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"below",
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"between",
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"under",
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"again",
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"further",
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"then",
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"once",
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"please",
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"thanks",
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"thank",
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"hello",
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"hi",
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"hey",
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"yes",
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"no",
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"tell",
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"give",
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"get",
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"got",
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])
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function tokenize(text: string) {
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return text
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.toLowerCase()
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.split(/[^a-z0-9]+/g)
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.map((t) => t.trim())
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.filter((t) => t.length >= 2)
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.filter((t) => t.length >= 2 && !STOPWORDS.has(t))
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}
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function scoreByTerms(text: string, terms: string[]) {
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