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*   Gradient AI

On this page

Gradient AI
===========

LangChain.js supports integration with Gradient AI. Check out [Gradient AI](https://docs.gradient.ai/docs) for a list of available models.

Setup[​](#setup "Direct link to Setup")
---------------------------------------

You'll need to install the official Gradient Node SDK as a peer dependency:

*   npm
*   Yarn
*   pnpm

    npm i @gradientai/nodejs-sdk

    yarn add @gradientai/nodejs-sdk

    pnpm add @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"});

Usage[​](#usage "Direct link to Usage")
---------------------------------------

tip

See [this section for general instructions on installing integration packages](/v0.2/docs/how_to/installation#installing-integration-packages).

*   npm
*   Yarn
*   pnpm

    npm install @langchain/community

    yarn add @langchain/community

    pnpm add @langchain/community

### Using Gradient's Base Models[​](#using-gradients-base-models "Direct link to Using Gradient's Base Models")

    import { GradientLLM } from "@langchain/community/llms/gradient_ai";// Note that inferenceParameters are optionalconst 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 });

#### API Reference:

*   [GradientLLM](https://v02.api.js.langchain.com/classes/langchain_community_llms_gradient_ai.GradientLLM.html) from `@langchain/community/llms/gradient_ai`

### Using your own fine-tuned Adapters[​](#using-your-own-fine-tuned-adapters "Direct link to 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 optionalconst 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 });

#### API Reference:

*   [GradientLLM](https://v02.api.js.langchain.com/classes/langchain_community_llms_gradient_ai.GradientLLM.html) from `@langchain/community/llms/gradient_ai`

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*   [Setup](#setup)
*   [Usage](#usage)
    *   [Using Gradient's Base Models](#using-gradients-base-models)
    *   [Using your own fine-tuned Adapters](#using-your-own-fine-tuned-adapters)

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