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Node.js Installation Guide

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Clarifai Node.js SDK

This is the official Node.js client for interacting with our powerful API. The Clarifai Node.js SDK offers a comprehensive set of tools to integrate Clarifai's AI platform to leverage computer vision capabilities like classification, detection, segmentation and natural language capabilities like classification, summarisation, generation, Q&A, etc into your applications. With just a few lines of code, you can leverage cutting-edge artificial intelligence to unlock valuable insights from visual and textual content.

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Installation

npm install clarifai-nodejs

Next.js Server Components

To use Clarifai Node.js in Next.js App Directory with server components, you will need to add clarifai-nodejs-grpc package (which is one of the primary dependency of Clarifai Node.js SDK) to the serverComponentsExternalPackages config of next.config.js

/** @type {import('next').NextConfig} */
const nextConfig = {
experimental: {
serverComponentsExternalPackages: ['clarifai-nodejs-grpc'],
},
}

module.exports = nextConfig

Usage

Clarifai uses Personal Access Tokens(PATs) to validate requests. You can create and manage PATs under your Clarifai account security settings.

  • 🔗 Create PAT: Log into Portal Profile Icon Security Settings Create Personal Access Token Set the scopes Confirm

Export your PAT as an environment variable. Then, import and initialize the API Client.

Set PAT as environment variable through terminal:

export CLARIFAI_PAT={your personal access token}

or use dotenv to load environment variables via a .env file

Using Models

Using the celebrity face recognition model to predict the celebrity in a given picture. For list of all available models visit clarifai models page.

import { Input, Model } from "clarifai-nodejs";

const input = Input.getInputFromUrl({
inputId: "test-image",
imageUrl:
"https://samples.clarifai.com/celebrity.jpeg",
});

const model = new Model({
authConfig: {
pat: process.env.CLARIFAI_PAT!,
userId: process.env.CLARIFAI_USER_ID!,
appId: process.env.CLARIFAI_APP_ID!
},
modelId: "celebrity-face-recognition",
});

model
.predict({
inputs: [input],
})
.then((response) => {
const result = response?.[0].data?.conceptsList[0].name ?? "unrecognized";
console.log(result);
})
.catch(console.error);

Using Workflows

Using a custom workflow built on clarifai.com to analyze sentiment of a given image. For list of all available workflows visit clarifai workflows page

import { Input, Workflow } from "clarifai-nodejs";

const input = Input.getInputFromUrl({
inputId: "test-image",
imageUrl:
"https://samples.clarifai.com/celebrity.jpeg",
});

const workflow = new Workflow({
authConfig: {
pat: process.env.CLARIFAI_PAT!,
userId: process.env.CLARIFAI_USER_ID!,
appId: process.env.CLARIFAI_APP_ID!
},
workflowId: "workflow-238a93",
});

workflow
.predict({
inputs: [input],
})
.then((response) => {
const result =
response.resultsList[0].outputsList[0].data?.regionsList[0].data
?.conceptsList[0].name ?? "unrecognized";
console.log(result);
})
.catch(console.error);

Listing available apps in an user account

On Clarifai, apps act as a central repository for models, datasets, inputs and other resources and information. Checkout how to create apps on clarifai portal.

import { User } from "clarifai-nodejs";

export const user = new User({
pat: process.env.CLARIFAI_PAT!,
userId: process.env.CLARIFAI_USER_ID!,
appId: process.env.CLARIFAI_APP_ID!,
});

const list = await user
.listApps({
pageNo: 1,
perPage: 20,
params: {
sortAscending: true,
},
})
.next();

const apps = list.value;
console.log(apps);

For full usage details, checkout our API Reference docs