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https://github.com/farcasclaudiu/Flowise.git
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add vector stores
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import { INode, INodeData, INodeParams } from '../../../src/Interface'
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import { getBaseClasses } from '../../../src/utils'
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import { VectorDBQAChain } from 'langchain/chains'
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import { BaseLanguageModel } from 'langchain/base_language'
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import { VectorStore } from 'langchain/vectorstores'
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class VectorDBQAChain_Chains 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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baseClasses: string[]
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description: string
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inputs: INodeParams[]
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constructor() {
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this.label = 'VectorDB QA Chain'
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this.name = 'vectorDBQAChain'
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this.type = 'VectorDBQAChain'
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this.icon = 'chain.svg'
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this.category = 'Chains'
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this.description = 'QA chain for vector databases'
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this.baseClasses = [this.type, ...getBaseClasses(VectorDBQAChain)]
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this.inputs = [
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{
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label: 'Language Model',
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name: 'model',
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type: 'BaseLanguageModel'
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},
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{
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label: 'Vector Store',
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name: 'vectorStore',
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type: 'VectorStore'
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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 BaseLanguageModel
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const vectorStore = nodeData.inputs?.vectorStore as VectorStore
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const chain = VectorDBQAChain.fromLLM(model, vectorStore)
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return chain
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}
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async run(nodeData: INodeData, input: string): Promise<string> {
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const chain = nodeData.instance as VectorDBQAChain
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const obj = {
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query: input
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}
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const res = await chain.call(obj)
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return res?.text
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}
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}
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module.exports = { nodeClass: VectorDBQAChain_Chains }
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@@ -0,0 +1,6 @@
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<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-dna" width="24" height="24" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round">
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<path stroke="none" d="M0 0h24v24H0z" fill="none"></path>
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<path d="M14.828 14.828a4 4 0 1 0 -5.656 -5.656a4 4 0 0 0 5.656 5.656z"></path>
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<path d="M9.172 20.485a4 4 0 1 0 -5.657 -5.657"></path>
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<path d="M14.828 3.515a4 4 0 0 0 5.657 5.657"></path>
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</svg>
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