Flowise/packages/components/nodes/embeddings/HuggingFaceInferenceEmbedding/HuggingFaceInferenceEmbeddi...

72 lines
2.6 KiB
TypeScript

import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { HuggingFaceInferenceEmbeddings, HuggingFaceInferenceEmbeddingsParams } from './core'
class HuggingFaceInferenceEmbedding_Embeddings 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 = 'HuggingFace Inference Embeddings'
this.name = 'huggingFaceInferenceEmbeddings'
this.version = 1.0
this.type = 'HuggingFaceInferenceEmbeddings'
this.icon = 'HuggingFace.svg'
this.category = 'Embeddings'
this.description = 'HuggingFace Inference API to generate embeddings for a given text'
this.baseClasses = [this.type, ...getBaseClasses(HuggingFaceInferenceEmbeddings)]
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
credentialNames: ['huggingFaceApi']
}
this.inputs = [
{
label: 'Model',
name: 'modelName',
type: 'string',
description: 'If using own inference endpoint, leave this blank',
placeholder: 'sentence-transformers/distilbert-base-nli-mean-tokens',
optional: true
},
{
label: 'Endpoint',
name: 'endpoint',
type: 'string',
placeholder: 'https://xyz.eu-west-1.aws.endpoints.huggingface.cloud/sentence-transformers/all-MiniLM-L6-v2',
description: 'Using your own inference endpoint',
optional: true
}
]
}
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
const modelName = nodeData.inputs?.modelName as string
const endpoint = nodeData.inputs?.endpoint as string
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const huggingFaceApiKey = getCredentialParam('huggingFaceApiKey', credentialData, nodeData)
const obj: Partial<HuggingFaceInferenceEmbeddingsParams> = {
apiKey: huggingFaceApiKey
}
if (modelName) obj.model = modelName
if (endpoint) obj.endpoint = endpoint
const model = new HuggingFaceInferenceEmbeddings(obj)
return model
}
}
module.exports = { nodeClass: HuggingFaceInferenceEmbedding_Embeddings }