Function retrieveMemory

packages/baseai/src/memory/retrieve.ts:17–108

({
	memory,
	query
}: {
	memory: string;
	query: string;
})

import { dlog } from '@/dev/utils/dlog';

export async function retrieveMemory({
	memory,
	query
}: {
	memory: string;
	query: string;
}) {
	p.intro(
		heading({
			text: 'RETRIEVE',
			sub: 'Retrieve similar chunks of a memory'
		})
	);

	// Spinner to show current action.
	const spin = p.spinner();

	try {
		if (!memory) {
			p.log.error(
				'Memory name is required. Use --memory or -m flag to specify.'
			);
			process.exit(1);
		}

		if (!query) {
			p.log.error(
				'Query is required. Use --query, or -q flag to specify.'
			);
			process.exit(1);
		}

		// 1- Check memory exists.
		const memoryName = validateMemoryName(memory); // Throws error if invalid so no need to check success
		await checkMemoryExists(memoryName);

		// 2- Load memory data.
		spin.start('Processing memory data...');
		const memoryChunks = await getDocumentsFromMemory([memory]);
		if (memoryChunks.length === 0)
			return p.log.error(
				'Please make sure the memory has one or more documents and they are embedded.'
			);

		// 3- Generate embeddings of query
		spin.message('Generating embeddings...');

		// Read config to determine which embedding to use.
		const config = await loadConfig();
		const useLocalEmbeddings = config.memory?.useLocalEmbeddings || false;

		let queryEmbedding = [];
		if (useLocalEmbeddings) {
			// Use local embeddings
			dlog('Generating local embeddings');
			queryEmbedding = await generateLocalEmbeddings([query]);
		} else {
			// Use OpenAI embeddings