monsterapi

monsterapi

monsterapi is a JavaScript client library for interacting with the Monster API. It provides an easy way to access the API's features and integrate them into your applications.

Available Models

Text Generation / Language Models (LLMs):

• falcon-7b-instruct
• mpt-7b-instruct
• llama2-7b-chat
• falcon-40b-instruct
• mpt-30b-instruct

Note: Other models are accessible through the client but are not activated yet. They will be updated shortly.

Image Generation:

• txt2img - stable-diffusion v1.5
• sdxl - stable-diffusion XL V1.0
• pix2pix - Instruct-pix2pix
• img2img - Image to Image using Stable Diffusion

Speech Generation:

• sunoai-bark - Bark (Sunoai Bark)
• whisper - Whisper Large V2

Usage

Installation

You can install the monsterapi package using npm or yarn:

npm install monsterapi

or

yarn add monsterapi

Import the Library

To use the monsterapi library in your project, import the MonsterApiClient class:

import  MonsterApiClient  from 'monsterapi';

or

const { default: MonsterApiClient } = require("monsterapi");

Initialize the Client

Create an instance of the MonsterApiClient class by providing your API key:

const client = new MonsterApiClient('your-api-key');

Replace 'your-api-key' with your actual Monster API key.

Get Response

You can use the get_response method to generate the Process Id of your request:

const model = 'whisper'; // Replace with a valid model name
const input = {
  // Replace with valid input data for the model
};

client.get_response(model, input)
  .then((result) => {
    // Handle the status response from the API
    console.log('Generated Data:', result);
  })
  .catch((error) => {
    // Handle API errors
    console.error('Error:', error);
  });

Check Status

You can use the get_status method to check the status of a Process Id:

const processId = 'your-process-id'; // Replace with the actual process ID

client.get_status(processId)
  .then((status) => {
    // Handle the status response from the API
    console.log('Status:', status);
  })
  .catch((error) => {
    // Handle API errors
    console.error('Error:', error);
  });

Wait and Get Result

You can use the wait_and_get_result method it take process id and wait till status get completed and retrieve the result:

const processId = 'your-process-id'; // Replace with the actual process ID

client.wait_and_get_result(processId)
  .then((result) => {
    // Handle the generated content result
    console.log('Generated content result:', result);
  })
  .catch((error) => {
    // Handle API errors or timeout
    console.error('Error:', error);
  });

Generate Content

You can use the generate method to retrive the result directly without using each function separately. generate method Generate the process Id and Retrive it Result :

const model = 'whisper'; // Replace with a valid model name
const input = {
  // Replace with valid input data for the model
};

client.generate(model, input)
  .then((response) => {
    // Handle the response from the API
    console.log('Generated content:', response);
  })
  .catch((error) => {
    // Handle API errors
    console.error('Error:', error);
  });

Handle File Upload From Local Device

Handle File Upload from you local computer to use generate and other method and retrive the result directly.

// Example for genrerating File Link and Using it in Model Object.

const model = 'img2img'; // Replace with a valid model name

const response = await client.uploadFile(selectedFile) // Put  selected file in `uploadFile Function`

const input = {
  // Replace with valid input data for the model

 
  file: response // put the response url in place of file url.
};

// Below is Example for Using Function separately 

client.uploadFile(file)
  .then((response) => {
    // Handle the response from the API
    console.log('Uploaded file:', response);
  })
  .catch((error) => {
    // Handle API errors
    console.error('Error:', error);
  });
  

// Please note that all files uploaded via the uploadFile function are automatically removed from the database for privacy and security purposes.

Documentation

For more details on the monsterapi library and its models, refer to the documentation.