104 lines
3.7 KiB
TypeScript
104 lines
3.7 KiB
TypeScript
import { INode, INodeData, INodeParams } from '../../../src/Interface'
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import { getBaseClasses } from '../../../src/utils'
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import { HFInput, HuggingFaceInference } from 'langchain/llms/hf'
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class HuggingFaceInference_LLMs implements INode {
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label: string
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name: string
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type: string
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icon: string
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category: string
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description: string
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baseClasses: string[]
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inputs: INodeParams[]
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constructor() {
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this.label = 'HuggingFace Inference'
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this.name = 'huggingFaceInference_LLMs'
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this.type = 'HuggingFaceInference'
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this.icon = 'huggingface.png'
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this.category = 'LLMs'
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this.description = 'Wrapper around HuggingFace large language models'
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this.baseClasses = [this.type, ...getBaseClasses(HuggingFaceInference)]
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this.inputs = [
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{
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label: 'Model',
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name: 'model',
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type: 'string',
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placeholder: 'gpt2'
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},
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{
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label: 'HuggingFace Api Key',
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name: 'apiKey',
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type: 'password'
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},
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{
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label: 'Temperature',
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name: 'temperature',
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type: 'number',
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description: 'Temperature parameter may not apply to certain model. Please check available model parameters',
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optional: true,
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additionalParams: true
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},
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{
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label: 'Max Tokens',
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name: 'maxTokens',
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type: 'number',
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description: 'Max Tokens parameter may not apply to certain model. Please check available model parameters',
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optional: true,
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additionalParams: true
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},
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{
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label: 'Top Probability',
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name: 'topP',
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type: 'number',
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description: 'Top Probability parameter may not apply to certain model. Please check available model parameters',
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optional: true,
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additionalParams: true
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},
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{
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label: 'Top K',
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name: 'hfTopK',
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type: 'number',
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description: 'Top K parameter may not apply to certain model. Please check available model parameters',
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optional: true,
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additionalParams: true
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},
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{
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label: 'Frequency Penalty',
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name: 'frequencyPenalty',
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type: 'number',
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description: 'Frequency Penalty parameter may not apply to certain model. Please check available model parameters',
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optional: true,
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additionalParams: true
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}
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]
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}
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async init(nodeData: INodeData): Promise<any> {
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const model = nodeData.inputs?.model as string
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const apiKey = nodeData.inputs?.apiKey as string
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const temperature = nodeData.inputs?.temperature as string
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const maxTokens = nodeData.inputs?.maxTokens as string
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const topP = nodeData.inputs?.topP as string
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const hfTopK = nodeData.inputs?.hfTopK as string
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const frequencyPenalty = nodeData.inputs?.frequencyPenalty as string
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const obj: Partial<HFInput> = {
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model,
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apiKey
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}
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if (temperature) obj.temperature = parseInt(temperature, 10)
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if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
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if (topP) obj.topP = parseInt(topP, 10)
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if (hfTopK) obj.topK = parseInt(hfTopK, 10)
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if (frequencyPenalty) obj.frequencyPenalty = parseInt(frequencyPenalty, 10)
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const huggingFace = new HuggingFaceInference(obj)
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return huggingFace
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}
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}
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module.exports = { nodeClass: HuggingFaceInference_LLMs }
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