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import { INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses } from '../../../src/utils'
import { OpenAI, OpenAIInput } from 'langchain/llms/openai'
class OpenAI_LLMs implements INode {
label: string
name: string
type: string
icon: string
category: string
description: string
baseClasses: string[]
inputs: INodeParams[]
constructor() {
this.label = 'OpenAI'
this.name = 'openAI'
this.type = 'OpenAI'
this.icon = 'openai.png'
this.category = 'LLMs'
this.description = 'Wrapper around OpenAI large language models'
this.baseClasses = [this.type, ...getBaseClasses(OpenAI)]
this.inputs = [
{
label: 'OpenAI Api Key',
name: 'openAIApiKey',
type: 'password'
},
{
label: 'Model Name',
name: 'modelName',
type: 'options',
options: [
{
label: 'text-davinci-003',
name: 'text-davinci-003'
},
{
label: 'text-davinci-002',
name: 'text-davinci-002'
},
{
label: 'text-curie-001',
name: 'text-curie-001'
},
{
label: 'text-babbage-001',
name: 'text-babbage-001'
}
],
default: 'text-davinci-003',
optional: true
},
{
label: 'Temperature',
name: 'temperature',
type: 'number',
default: 0.7,
optional: true
},
{
label: 'Max Tokens',
name: 'maxTokens',
type: 'number',
optional: true,
additionalParams: true
},
{
label: 'Top Probability',
name: 'topP',
type: 'number',
optional: true,
additionalParams: true
},
{
label: 'Best Of',
name: 'bestOf',
type: 'number',
optional: true,
additionalParams: true
},
{
label: 'Frequency Penalty',
name: 'frequencyPenalty',
type: 'number',
optional: true,
additionalParams: true
},
{
label: 'Presence Penalty',
name: 'presencePenalty',
type: 'number',
optional: true,
additionalParams: true
},
{
label: 'Batch Size',
name: 'batchSize',
type: 'number',
optional: true,
additionalParams: true
},
{
label: 'Timeout',
name: 'timeout',
type: 'number',
optional: true,
additionalParams: true
},
{
label: 'BasePath',
name: 'basepath',
type: 'string',
optional: true,
additionalParams: true
}
]
}
async init(nodeData: INodeData): Promise<any> {
const temperature = nodeData.inputs?.temperature as string
const modelName = nodeData.inputs?.modelName as string
const openAIApiKey = nodeData.inputs?.openAIApiKey as string
const maxTokens = nodeData.inputs?.maxTokens as string
const topP = nodeData.inputs?.topP as string
const frequencyPenalty = nodeData.inputs?.frequencyPenalty as string
const presencePenalty = nodeData.inputs?.presencePenalty as string
const timeout = nodeData.inputs?.timeout as string
const batchSize = nodeData.inputs?.batchSize as string
const bestOf = nodeData.inputs?.bestOf as string
const streaming = nodeData.inputs?.streaming as boolean
const basePath = nodeData.inputs?.basepath as string
const obj: Partial<OpenAIInput> & { openAIApiKey?: string } = {
temperature: parseInt(temperature, 10),
modelName,
openAIApiKey,
streaming: streaming ?? true
}
if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
if (topP) obj.topP = parseInt(topP, 10)
if (frequencyPenalty) obj.frequencyPenalty = parseInt(frequencyPenalty, 10)
if (presencePenalty) obj.presencePenalty = parseInt(presencePenalty, 10)
if (timeout) obj.timeout = parseInt(timeout, 10)
if (batchSize) obj.batchSize = parseInt(batchSize, 10)
if (bestOf) obj.bestOf = parseInt(bestOf, 10)
const model = new OpenAI(obj, {
basePath
})
return model
}
}
module.exports = { nodeClass: OpenAI_LLMs }
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