LangChain.js supports integration with Gradient AI. Check out Gradient AI for a list of available models.

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Setup

You’ll need to install the official Gradient Node SDK as a peer dependency:
npm
npm i @gradientai/nodejs-sdk
You will need to set the following environment variables for using the Gradient AI API.
  1. GRADIENT_ACCESS_TOKEN
  2. GRADIENT_WORKSPACE_ID
Alternatively, these can be set during the GradientAI Class instantiation as gradientAccessKey and workspaceId respectively. For example: 
const model = new GradientLLM({
  gradientAccessKey: "My secret Access Token"
  workspaceId: "My secret workspace id"
});

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Usage

See this section for general instructions on installing LangChain packages.
npm
npm install @langchain/community @langchain/core

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Using Gradient’s Base Models

import { GradientLLM } from "@langchain/community/llms/gradient_ai";

// Note that inferenceParameters are optional
const model = new GradientLLM({
  modelSlug: "llama2-7b-chat",
  inferenceParameters: {
    maxGeneratedTokenCount: 20,
    temperature: 0,
  },
});
const res = await model.invoke(
  "What would be a good company name for a company that makes colorful socks?"
);

console.log({ res });

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Using your own fine-tuned Adapters

The use your own custom adapter simply set adapterId during setup. 
import { GradientLLM } from "@langchain/community/llms/gradient_ai";

// Note that inferenceParameters are optional
const model = new GradientLLM({
  adapterId: process.env.GRADIENT_ADAPTER_ID,
  inferenceParameters: {
    maxGeneratedTokenCount: 20,
    temperature: 0,
  },
});
const res = await model.invoke(
  "What would be a good company name for a company that makes colorful socks?"
);

console.log({ res });