Gradient AI
LangChain.js supports integration with Gradient AI. Check out Gradient AI for a list of available models.
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.
GRADIENT_ACCESS_TOKEN
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
- npm
- Yarn
- pnpm
npm install @langchain/community @langchain/core
yarn add @langchain/community @langchain/core
pnpm add @langchain/community @langchain/core
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 });
API Reference:
- GradientLLM from
@langchain/community/llms/gradient_ai
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 });
API Reference:
- GradientLLM from
@langchain/community/llms/gradient_ai
Related
- LLM conceptual guide
- LLM how-to guides