212 lines
8.2 KiB
JavaScript
212 lines
8.2 KiB
JavaScript
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"use strict";
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Object.defineProperty(exports, "__esModule", { value: true });
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exports.TurbopufferVectorStore = void 0;
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const uuid_1 = require("uuid");
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const documents_1 = require("@langchain/core/documents");
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const async_caller_1 = require("@langchain/core/utils/async_caller");
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const chunk_array_1 = require("@langchain/core/utils/chunk_array");
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const env_1 = require("@langchain/core/utils/env");
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const vectorstores_1 = require("@langchain/core/vectorstores");
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class TurbopufferVectorStore extends vectorstores_1.VectorStore {
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get lc_secrets() {
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return {
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apiKey: "TURBOPUFFER_API_KEY",
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};
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}
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get lc_aliases() {
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return {
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apiKey: "TURBOPUFFER_API_KEY",
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};
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}
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// Handle minification for tracing
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static lc_name() {
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return "TurbopufferVectorStore";
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}
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_vectorstoreType() {
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return "turbopuffer";
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}
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constructor(embeddings, args) {
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super(embeddings, args);
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Object.defineProperty(this, "distanceMetric", {
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enumerable: true,
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configurable: true,
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writable: true,
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value: "cosine_distance"
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});
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Object.defineProperty(this, "apiKey", {
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enumerable: true,
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configurable: true,
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writable: true,
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value: void 0
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});
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Object.defineProperty(this, "namespace", {
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enumerable: true,
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configurable: true,
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writable: true,
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value: "default"
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});
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Object.defineProperty(this, "apiUrl", {
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enumerable: true,
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configurable: true,
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writable: true,
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value: "https://api.turbopuffer.com/v1"
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});
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Object.defineProperty(this, "caller", {
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enumerable: true,
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configurable: true,
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writable: true,
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value: void 0
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});
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Object.defineProperty(this, "batchSize", {
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enumerable: true,
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configurable: true,
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writable: true,
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value: 3000
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});
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const { apiKey: argsApiKey, namespace, distanceMetric, apiUrl, batchSize, ...asyncCallerArgs } = args;
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const apiKey = argsApiKey ?? (0, env_1.getEnvironmentVariable)("TURBOPUFFER_API_KEY");
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if (!apiKey) {
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throw new Error(`Turbopuffer API key not found.\nPlease pass it in as "apiKey" or set it as an environment variable called "TURBOPUFFER_API_KEY"`);
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}
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this.apiKey = apiKey;
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this.namespace = namespace ?? this.namespace;
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this.distanceMetric = distanceMetric ?? this.distanceMetric;
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this.apiUrl = apiUrl ?? this.apiUrl;
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this.batchSize = batchSize ?? this.batchSize;
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this.caller = new async_caller_1.AsyncCaller({
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maxConcurrency: 6,
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maxRetries: 0,
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...asyncCallerArgs,
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});
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}
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defaultHeaders() {
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return {
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Authorization: `Bearer ${this.apiKey}`,
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"Content-Type": "application/json",
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};
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}
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async callWithRetry(fetchUrl, stringifiedBody, method = "POST") {
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const json = await this.caller.call(async () => {
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const headers = {
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Authorization: `Bearer ${this.apiKey}`,
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};
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if (stringifiedBody !== undefined) {
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headers["Content-Type"] = "application/json";
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}
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const response = await fetch(fetchUrl, {
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method,
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headers,
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body: stringifiedBody,
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});
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if (response.status !== 200) {
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const error = new Error(`Failed to call turbopuffer. Response status ${response.status}\nFull response: ${await response.text()}`);
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// eslint-disable-next-line @typescript-eslint/no-explicit-any
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error.response = response;
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throw error;
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}
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return response.json();
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});
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return json;
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}
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async addVectors(vectors, documents, options) {
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if (options?.ids && options.ids.length !== vectors.length) {
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throw new Error("Number of ids provided does not match number of vectors");
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}
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if (documents.length !== vectors.length) {
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throw new Error("Number of documents provided does not match number of vectors");
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}
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if (documents.length === 0) {
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throw new Error("No documents provided");
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}
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const batchedVectors = (0, chunk_array_1.chunkArray)(vectors, this.batchSize);
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const batchedDocuments = (0, chunk_array_1.chunkArray)(documents, this.batchSize);
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const batchedIds = options?.ids
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? (0, chunk_array_1.chunkArray)(options.ids, this.batchSize)
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: batchedDocuments.map((docs) => docs.map((_) => (0, uuid_1.v4)()));
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const batchRequests = batchedVectors.map(async (batchVectors, index) => {
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const batchDocs = batchedDocuments[index];
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const batchIds = batchedIds[index];
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if (batchIds.length !== batchVectors.length) {
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throw new Error("Number of ids provided does not match number of vectors");
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}
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const attributes = {
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__lc_page_content: batchDocs.map((doc) => doc.pageContent),
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};
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const usedMetadataFields = new Set(batchDocs.map((doc) => Object.keys(doc.metadata)).flat());
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for (const key of usedMetadataFields) {
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attributes[key] = batchDocs.map((doc) => {
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if (doc.metadata[key] !== undefined) {
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if (typeof doc.metadata[key] === "string") {
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return doc.metadata[key];
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}
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else {
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console.warn([
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`[WARNING]: Dropping non-string metadata key "${key}" with value "${JSON.stringify(doc.metadata[key])}".`,
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`turbopuffer currently supports only string metadata values.`,
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].join("\n"));
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return null;
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}
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}
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else {
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return null;
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}
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});
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}
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const data = {
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ids: batchIds,
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vectors: batchVectors,
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attributes,
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};
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return this.callWithRetry(`${this.apiUrl}/vectors/${this.namespace}`, JSON.stringify(data));
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});
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// Execute all batch requests in parallel
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await Promise.all(batchRequests);
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return batchedIds.flat();
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}
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async delete(params) {
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if (params.deleteIndex) {
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await this.callWithRetry(`${this.apiUrl}/vectors/${this.namespace}`, undefined, "DELETE");
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}
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else {
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throw new Error(`You must provide a "deleteIndex" flag.`);
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}
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}
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async addDocuments(documents, options) {
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const vectors = await this.embeddings.embedDocuments(documents.map((doc) => doc.pageContent));
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return this.addVectors(vectors, documents, options);
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}
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async queryVectors(query, k, includeVector,
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// See https://Turbopuffer.com/docs/reference/query for more info
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filter) {
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const data = {
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vector: query,
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top_k: k,
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distance_metric: this.distanceMetric,
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filters: filter,
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include_attributes: true,
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include_vectors: includeVector,
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};
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return this.callWithRetry(`${this.apiUrl}/vectors/${this.namespace}/query`, JSON.stringify(data));
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}
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async similaritySearchVectorWithScore(query, k, filter) {
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const search = await this.queryVectors(query, k, false, filter);
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const result = search.map((res) => {
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const { __lc_page_content, ...metadata } = res.attributes;
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return [
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new documents_1.Document({
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pageContent: __lc_page_content,
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metadata,
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}),
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res.dist,
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];
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});
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return result;
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}
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static async fromDocuments(docs, embeddings, dbConfig) {
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const instance = new this(embeddings, dbConfig);
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await instance.addDocuments(docs);
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return instance;
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}
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}
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exports.TurbopufferVectorStore = TurbopufferVectorStore;
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