import { getBaseClasses, getCredentialData, getCredentialParam, ICommonObject, INode, INodeData, INodeParams } from '../../../src' import { OpenAI } from '@langchain/openai' import { BaseCache } from '@langchain/core/caches' class Sambanova_LLMs implements INode { label: string name: string version: number type: string icon: string category: string description: string baseClasses: string[] credential: INodeParams inputs: INodeParams[] constructor() { this.label = 'Sambanova' this.name = 'sambanova' this.version = 1.0 this.type = 'Sambanova' this.icon = 'sambanova.png' this.category = 'LLMs' this.description = 'Wrapper around Sambanova API for large language models' this.baseClasses = [this.type, ...getBaseClasses(OpenAI)] this.credential = { label: 'Connect Credential', name: 'credential', type: 'credential', credentialNames: ['sambanovaApi'] } this.inputs = [ { label: 'Cache', name: 'cache', type: 'BaseCache', optional: true }, { label: 'Model Name', name: 'modelName', type: 'string', default: 'Meta-Llama-3.3-70B-Instruct', description: 'For more details see https://docs.sambanova.ai/cloud/docs/get-started/supported-models', optional: true } ] } async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { const cache = nodeData.inputs?.cache as BaseCache const modelName = nodeData.inputs?.modelName as string const credentialData = await getCredentialData(nodeData.credential ?? '', options) const sambanovaKey = getCredentialParam('sambanovaApiKey', credentialData, nodeData) const obj: any = { model: modelName, configuration: { baseURL: 'https://api.sambanova.ai/v1', apiKey: sambanovaKey } } if (cache) obj.cache = cache const sambanova = new OpenAI(obj) return sambanova } } module.exports = { nodeClass: Sambanova_LLMs }