64 lines
2.2 KiB
TypeScript
64 lines
2.2 KiB
TypeScript
import { INode, INodeData, INodeParams } from '../../../src/Interface'
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import { getBaseClasses } from '../../../src/utils'
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import { HuggingFaceInferenceEmbeddings, HuggingFaceInferenceEmbeddingsParams } from '@langchain/community/dist/embeddings/hf.cjs'
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class HuggingFaceInferenceEmbedding_Embeddings 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 Embeddings'
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this.name = 'huggingFaceInferenceEmbeddings'
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this.type = 'HuggingFaceInferenceEmbeddings'
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this.icon = 'huggingface.png'
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this.category = 'Embeddings'
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this.description = 'HuggingFace Inference API to generate embeddings for a given text'
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this.baseClasses = [this.type, ...getBaseClasses(HuggingFaceInferenceEmbeddings)]
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this.inputs = [
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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: 'Model',
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name: 'modelName',
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type: 'string',
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optional: true
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},
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{
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label: 'Endpoint',
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name: 'endpoint',
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type: 'string',
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placeholder: 'https://xyz.eu-west-1.aws.endpoints.huggingface.cloud/sentence-transformers/all-MiniLM-L6-v2',
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description: 'Using your own inference endpoint',
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optional: 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 apiKey = nodeData.inputs?.apiKey as string
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const modelName = nodeData.inputs?.modelName as string
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const endpoint = nodeData.inputs?.endpoint as string
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const obj: Partial<HuggingFaceInferenceEmbeddingsParams> = {
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apiKey
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}
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if (modelName) obj.model = modelName
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if (endpoint) obj.endpointUrl = endpoint
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const model = new HuggingFaceInferenceEmbeddings(obj)
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return model
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}
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}
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module.exports = { nodeClass: HuggingFaceInferenceEmbedding_Embeddings }
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