JavaScript SDK Documentation Page

Installation

Intall Modzy's JavaScript SDK with NPM

npm install @modzy/modzy-sdk

or YARN

yarn add @modzy/modzy-sdk

Usage/Examples

Initializing the SDK

Initialize your client by authenticating with an API key. You can download an API Key from your instance of Modzy.

import { ModzyClient } from "@modzy/modzy-sdk";

const modzyClient = new ModzyClient({
  apiKey: "Valid Modzy API Key", //e.g., "JbFkWZMx4Ea3epIrxSgA.a2fR36fZi3sdFPoztAXT"
  url: "Valid Modzy URL", //e.g., "https://trial.app.modzy.com"
});

Running Inferences

Raw Text Inputs

Submit an inference job to a text-based model by providing the model ID, version, and raw input text.

//Submit text to v1.0.1 of a Sentiment Analysis model, and to make the job explainable, change explain=True
const { jobIdentifier } = await modzyClient.submitJobText({
  modelId: "ed542963de",
  version: "1.0.1",
  sources: {
    firstPhoneCall: {
      "input.txt": "Mr Watson, come here. I want to see you.",
    },
  },
});

File Inputs

Pass a file from your local directory to a model by providing the model ID, version, and the filepath of your sample data:

// Submit a job to the Image-Based Geolocation model
const { jobIdentifier } = await modzyClient.submitJobFile({
  modelId: "aevbu1h3yw",
  version: "1.0.1",
  sources: {
    nyc-skyline: {
      image: "./images/nyc-skyline.jpg",
    },
  },
});

Embedded Inputs

Convert images and other large inputs to base64 embedded data and submit to a model by providing a model ID, version number, and dictionary with one or more base64 encoded inputs:

const fs = require('fs');

//Embed input as a string in base64
const imageBytes = fs.readFileSync('images/tower-bridge.jpg');
//Prepare the source dictionary
let sources = { "tower-bridge": { "image": imageBytes } };

//Submit the image to v1.0.1 of an Imaged-based Geolocation model
const { jobIdentifier } = await modzyClient.submitJobEmbedded("aevbu1h3yw", "1.0.1", "application/octet-stream", sources);

Inputs from Databases

Submit data from a SQL database to a model by providing a model ID, version, a SQL query, and database connection credentials:

//Add database connection and query information
const dbUrl = "jdbc:postgresql://db.bit.io:5432/bitdotio"
const dbUserName = DB_USER_NAME;
const dbPassword = DB_PASSWORD;
const dbDriver = "org.postgresql.Driver";
//Select as "input.txt" becase that is the required input name for this model
const dbQuery = "SELECT \"mailaddr\" as \"input.txt\" FROM \"user/demo_repo\".\"atl_parcel_attr\" LIMIT 10;";

//Submit the database query to v0.0.12 of a Named Entity Recognition model
const { jobIdentifier } = await modzyClient.submitJobJDBC("a92fc413b5", "0.0.12", dbUrl, dbUserName, dbPassword, dbDriver, dbQuery)}

Inputs from Cloud Storage

Submit data directly from your cloud storage bucket (Amazon S3 supported) by providing a model ID, version, and storage-blob-specific parameters.

AWS S3

//Define sources dictionary with bucket and key that points to the correct file in your s3 bucket
const bucketName = "s3-bucket-name";
const fileKey = "key-to-file.txt";
let sources = { "sampleText": { "input.txt": { 'bucket': bucketName, 'key': fileKey } } };

const accessKey = ACCESS_KEY_ID;
const secretAccessKey = SECRET_KEY;
const region = "us-east-1";

//Submit s3 input to v1.0.1 of a Sentiment Analysis model
const { jobIdentifier } = await modzyClient.submitJobAWSS3("ed542963de", "1.0.1", accessKey, secretAccessKey, region, sources)

Getting Results

Hold until the inference is complete:

await modzyClient.blockUntilJobComplete(jobIdentifier);

Get the output results:

const result = await modzyClient.getResult(jobIdentifier);

SDK Code Examples

• samples provides details for specific use cases and are intended to be run using Node.js, but most can also run in the browser
• react examples contains react components that can be used to the browser to send files to, or retrieve files from Modzy.

To run these examples, make sure to update API_KEY and MODZY_URL to valid values.

Running Tests

The Jest tests expect that there is a .env file at the root of the repo that contains a valid Modzy api key like this:

API_KEY=xxxxxxxxxxxxxxxxxxxx.xxxxxxxxxxxxxxxxxxxx

Documentation

Modzy's SDK is built on top of the Modzy HTTP/REST API. For a full list of features and supported routes visit JavaScript SDK on docs.modzy.com

Support

For support, email opensource@modzy.com or join our Slack.

Contributing

Contributions are always welcome!

See contributing.md for ways to get started.

Please adhere to this project's code of conduct.

We are happy to receive contributions from all of our users. Check out our contributing file to learn more.