Aquila JS

Javascript client to access Aquila Network Neural Search Engine

Here is a bird's eye view of where Aquila Client Libraries fit in the entire ecosystem:

Connect to Database and Hub

import { AquilaClient, Wallet, Db, Hub } from 'aquila-js';

const wallet = new Wallet('DB_PRIVATE_KEY_PATH-HERE');
const dbUrl = 'DB_URL-HERE';
const dbPort = 'DB_PORT--HERE';
const hubWallet = new Wallet('HUB_PRIVATE_KEY_PATH-HERE');
const hubUrl = 'HUB_URL-HERE';
const hubPort = 'HUB_PORT-HERE';

// connecting to aquila db server
AquilaClient.getDbServer(dbUrl, dbPort, wallet).then(db => {
	// connected
});
// connecting to aquila hub server
AquilaClient.getHubServer(hubUrl, hubPort, hubWallet).then(hub => {
	// connected
});

Create Database

const schema: Schema = {
	description: "description of db",
	unique: "r8and0mse---",
	encoder: "ftxt:https://encoder-url",
	codelen: 500,
	metadata: {
			"key": "value",
	}
};
db.createDatabase(schema).then(dbName => {
	// done
})
hub.createDatabase(schema).then(dbNameHub => {
	// done
})

Create Document

const dbName = 'db-name';
const data = ['Amazon', 'Google'];
const generatedCode = hub.compressDocument(dbName, data).then((generatedCode: as number[][]) => {
const docs: Document<DocMetaData>[] = [
	{
		metadata: {
				name: "name test",
				age: 20
		},
		code: generatedCode[0],
	},{
		metadata: {
				name: "name2 test",
				age: 32
		},
		code: generatedCode[1],
	}
];
	return db.createDocuments(dbName, docs)
}).then(docs => {
	// succes	
});
	

Search Documents

const searchData = [[0.06443286, 0.106639  , 0.81865615]];
const resultCount = 10;
db.searchKDocuments<DocMetaData>(dbName[0], searchData, resultCount).then(result => {
	// success
});

Delete Document

db.deleteDocuments(dbName[0], deleteIds).then(result => {
// success
});