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edit (content): add script refs for custom js
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‎content/docs/pipelines/how-to/ecommerce-search.md‎

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@@ -95,6 +95,240 @@ This guide shows how to implement an e-commerce search pipeline that:
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]
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```
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Script: generateRequest.js
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```js
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function handleRequest() {
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const queryTerm = context.envs.query;
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/* verifying that format of query is as expected before modifying */
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const requestBody = JSON.parse(context.request.body);
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if (!requestBody.query || requestBody.query.length == 0) {
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/* Update the queries with the defaultQuery */
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requestBody.query.forEach((queryEach, queryIndex) => {
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console.log("query id each: ", queryEach["id"]);
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if (
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queryEach.type == "suggestion" ||
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queryEach.type == "search" ||
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queryEach.type == undefined ||
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queryEach.type == "term"
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) {
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requestBody.query[queryIndex] = injectDefaultQuery(queryEach);
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}
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});
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return {
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request: { body: JSON.stringify(requestBody) }
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};
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}
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/* If there is only one query and it is a suggestion type of
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* query, we need to inject a `result` id query where there will
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* be the defaultQuery and the current `search` query will react to
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* it.
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**/
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if (
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requestBody.query.length == 1 &&
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requestBody.query[0].type == "suggestion" &&
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requestBody.query[0].id == "search"
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) {
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requestBody.query[0].id = "result";
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requestBody.query[0].execute = false;
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let resultQuery = {
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...requestBody.query[0],
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id: "search",
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react: { and: ["result"] },
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execute: true
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};
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requestBody.query.push(resultQuery);
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}
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/* Iterate through and if there is a suggestion or search query, update it
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* with the extra fields.
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**/
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console.log("query length: ", requestBody.query.length);
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requestBody.query.forEach((queryEach, queryIndex) => {
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console.log("query id: ", queryEach["id"]);
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/* If there is a term query of id result, change it to `search` type */
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if (queryEach.id == "result" && queryEach.type == "term") {
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queryEach.type = "search";
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}
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if (queryEach.type == "suggestion") {
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console.log("query id: ", queryEach["id"]);
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requestBody.query[queryIndex] = updateSuggestionsQuery(queryTerm, queryEach);
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} else if (queryEach.type == "search") {
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requestBody.query[queryIndex] = updateSearchQuery(queryTerm, queryEach);
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console.log(JSON.stringify(requestBody.query[queryIndex]));
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}
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/* Inject the defaultQuery
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*
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* If there is only one query, we don't want defaultQuery to
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* be injected since that will override the main query.
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*/
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console.log(queryEach.id, ": ", queryEach.type);
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if (
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requestBody.query.length > 1 &&
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(queryEach.type == "suggestion" ||
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queryEach.type == "search" ||
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queryEach.type == undefined ||
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queryEach.type == "term")
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) {
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requestBody.query[queryIndex] = injectDefaultQuery(queryEach);
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}
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});
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return {
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request: { body: JSON.stringify(requestBody) }
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};
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}
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function updateSuggestionsQuery(queryTerm, suggestionQuery) {
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if (!queryTerm) queryTerm = "";
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const queryLength = queryTerm.length;
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const dataFields = [
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{ field: "longDescription", weight: 0.5 },
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{ field: "name", weight: 3 },
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{ field: "name.autosuggest",weight: 0.1 },
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{ field: "name.search", weight: 0.01},
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{ field: "class", weight: 5 },
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{ field: "class.search", weight: 1 }
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];
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suggestionQuery["dataField"] = dataFields;
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suggestionQuery["queryFormat"] = "and";
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suggestionQuery["includeFields"] = [
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"class", "globalRank", "categoryRank", "name",
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"shortDescription", "longDescription", "salePrice", "image"
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];
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suggestionQuery["distinctField"] = "class.keyword";
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suggestionQuery["distinctFieldConfig"] = {
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inner_hits: {
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name: "rel",
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size: 2,
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_source: [
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"class", "globalRank", "categoryRank", "name",
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"shortDescription", "longDescription", "salePrice", "image"
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]
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}
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};
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console.log("query id: ", suggestionQuery["id"]);
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/* Responding to the user intent based on the query length */
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if (queryLength <= 4) {
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// user is perhaps checking out the search
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suggestionQuery.enablePopularSuggestions = true;
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suggestionQuery.enableFeaturedSuggestions = true;
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suggestionQuery.enableRecentSuggestions = true;
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} else if (queryLength >= 5 && queryLength <= 9) {
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// user is looking for something specific
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suggestionQuery.enablePopularSuggestions = false;
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suggestionQuery.enableFeaturedSuggestions = false;
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suggestionQuery.enableRecentSuggestions = true;
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} else if (queryLength >= 10) {
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// user is definitely looking for something specific
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suggestionQuery.enableRecentSuggestions = false;
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suggestionQuery.enablePopularSuggestions = false;
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suggestionQuery.enableFeaturedSuggestions = false;
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}
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return suggestionQuery;
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}
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function updateSearchQuery(queryTerm, searchQuery) {
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const dataFields = [
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{ field: "longDescription", weight: 1 },
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{ field: "name", weight: 3 },
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{ field: "name.autosuggest",weight: 0.2 },
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{ field: "name.delimiter", weight: 1 },
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{ field: "name.search", weight: 0.1 },
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{ field: "class", weight: 5 },
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{ field: "class.search", weight: 1 }
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];
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searchQuery["dataField"] = dataFields;
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searchQuery["queryFormat"] = "and";
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searchQuery["includeFields"] = [
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"class", "globalRank", "categoryRank", "name",
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"shortDescription", "longDescription", "salePrice", "image"
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];
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searchQuery["distinctField"] = "class.keyword";
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searchQuery["distinctFieldConfig"] = {
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inner_hits: {
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name: "rel",
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size: 2,
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_source: [
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"class", "globalRank", "categoryRank", "name",
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"shortDescription", "longDescription", "salePrice", "image"
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]
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}
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};
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/*searchQuery['sortField'] = ['globalRank', 'categoryRank'];
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searchQuery['sortBy'] = 'asc'; */
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console.log("query is: ", searchQuery["id"]);
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console.log("datafields are: ", JSON.stringify(searchQuery["dataField"]));
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if (!queryTerm) return searchQuery;
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const queryLength = queryTerm.length;
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if (!queryTerm || queryLength === 0) return searchQuery;
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if (
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queryLength >= 20 &&
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queryTerm.split(" ").length >= 4 &&
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queryTerm[queryTerm.length - 1] == "?"
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) {
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searchQuery["enableAI"] = true;
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searchQuery["execute"] = true;
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}
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return searchQuery;
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}
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function injectDefaultQuery(query) {
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/* Use exists query to boost score of results that contain
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either globalRank or categoryRank */
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console.log("existing default query: ", JSON.stringify(query.defaultQuery));
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if (
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(!query.defaultQuery || JSON.stringify(query.defaultQuery) == "{}") &&
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query.execute
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) {
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query.defaultQuery = {
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query: {
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bool: {
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must_not: [
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{ match: { class: "ACCY" } },
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{ match: { class: "APPLECARE" } },
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{ match: { class: "ACCESSORIES" } },
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{ match: { class: "ACCESS." } },
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{ match: { class: "IPAD MONTHLY"} },
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{ match: { class: "SVC FEE" } }
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],
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should: [
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{ range: { salePrice: { gte: 499, boost: 5 } } },
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{ range: { salePrice: { gte: 299, boost: 5 } } },
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{ range: { salePrice: { gte: 99, boost: 4 } } },
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{ range: { categoryRank:{ lte: 10, boost: 2 } } },
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{ range: { categoryRank:{ lte: 5, boost: 2 } } },
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{ range: { categoryRank:{ lte: 1, boost: 1 } } },
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{ range: { globalRank: { lte: 10, boost: 5 } } },
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{ range: { salePrice: { gte: 50, boost: 0.01 } } }
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]
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}
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}
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};
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}
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return query;
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}
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```
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### 3) First pass: RS → ES
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```json
@@ -127,6 +361,81 @@ This guide shows how to implement an e-commerce search pipeline that:
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]
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```
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Script: checkTypo.js
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```js
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function handleRequest() {
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const queryTerm = context.envs.query;
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if (queryTerm && queryTerm.length < 5) {
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return {};
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}
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const globalRankWeight = 0.2;
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const categoryRankWeight = 0.5;
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const responseBody = JSON.parse(context.response.body);
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if (
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responseBody.search?.hits?.hits?.length != 0 &&
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responseBody.result?.hits?.hits?.length != 0
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) {
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/* We have hits: re-score using rank signals */
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const results = responseBody.result?.hits?.hits;
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if (results) {
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results.forEach((hitEach, hitIndex) => {
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if (!hitEach._source.categoryRank && !hitEach._source.globalRank) {
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hitEach._source.categoryRank = 10;
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}
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let isGlobalRank = false;
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if (hitEach._source.globalRank) {
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const ogScore = hitEach._score;
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results[hitIndex]._score =
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ogScore - globalRankWeight * hitEach._source.globalRank;
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isGlobalRank = true;
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}
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if (hitEach._source.categoryRank && !isGlobalRank) {
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const ogScore = hitEach._score;
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results[hitIndex]._score =
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ogScore - categoryRankWeight * hitEach._source.categoryRank;
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}
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});
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/* Sort descending by updated score */
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results.sort((a, b) => b._score - a._score);
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responseBody.result.hits.hits = results;
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return {
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response: { body: JSON.stringify(responseBody) }
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};
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}
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return {};
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}
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/* No hits: enable fuzzy fallback and trigger research pass */
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const rsBody = JSON.parse(context.envs["ORIGINAL_RS_BODY"]);
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let fuzziness = 1;
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if (queryTerm.length >= 5 && queryTerm.length <= 9) {
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fuzziness = 1;
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} else {
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fuzziness = 2;
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}
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rsBody.query?.forEach((queryEach, queryIndex) => {
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queryEach.fuzziness = fuzziness;
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rsBody.query[queryIndex] = queryEach;
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});
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return {
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request: { body: JSON.stringify(rsBody) },
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envs: { research: true, ...context.envs }
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};
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}
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```
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### 5) Second pass (conditional)
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```json

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