hnswsqlite/src/cli/commands/add.ts

Vector search with HNSWlib and SQLite in TypeScript.

import { VectorStore } from '../../vectorStore';
import inquirer from 'inquirer';

export async function addDocument(store: VectorStore, text: string, embedding?: string[]): Promise<number> {
  let vector: number[] = [];
  
  // If embedding is not provided, ask if user wants to generate one
  if (!embedding || embedding.length === 0) {
    const { useDummy } = await inquirer.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);
}