hnswsqlite/dist/cli/commands/add.js

Vector search with HNSWlib and SQLite in TypeScript.

"use strict";
var __importDefault = (this && this.__importDefault) || function (mod) {
    return (mod && mod.__esModule) ? mod : { "default": mod };
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.addDocument = addDocument;
const inquirer_1 = __importDefault(require("inquirer"));
async function addDocument(store, text, embedding) {
    let vector = [];
    // If embedding is not provided, ask if user wants to generate one
    if (!embedding || embedding.length === 0) {
        const { useDummy } = await inquirer_1.default.prompt([{
                type: 'confirm',
                name: 'useDummy',
                message: 'No embedding provided. Use dummy embedding?',
                default: true
            }]);
        if (useDummy) {
            // Create a dummy embedding of the correct dimension
            const dim = store['dim'];
            vector = new Array(dim).fill(0.1);
        }
        else {
            throw new Error('Embedding is required');
        }
    }
    else {
        // Parse the provided embedding
        vector = embedding.map(Number);
    }
    // Add the document to the store
    return store.addDocument(text, vector);
}