clarifai-nodejs

Clarifai Node.js SDK

This library is currently in developer preview, any improvements & feedback welcome!

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

Changelog

0.0.3 (2024-07-02)

Features

• custom root certificate support (#19) (8b517f4)
• RAG Module (#9) (7354e93)

Bug Fixes

• updated methods to match docs (#14) (3d46b72)