mirror of
https://github.com/farcasclaudiu/Flowise.git
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Merge pull request #236 from FlowiseAI/revert-209-feature/FaissVS
Revert "Feature/Add faiss"
This commit is contained in:
@@ -1,70 +0,0 @@
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import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
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import { FaissStore } from 'langchain/vectorstores/faiss'
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import { Embeddings } from 'langchain/embeddings/base'
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import { getBaseClasses } from '../../../src/utils'
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class Faiss_Existing_VectorStores implements INode {
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label: string
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name: string
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description: 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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inputs: INodeParams[]
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outputs: INodeOutputsValue[]
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constructor() {
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this.label = 'Faiss Load Existing Index'
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this.name = 'faissExistingIndex'
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this.type = 'Faiss'
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this.icon = 'faiss.svg'
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this.category = 'Vector Stores'
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this.description = 'Load existing index from Faiss (i.e: Document has been upserted)'
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this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
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this.inputs = [
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{
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label: 'Embeddings',
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name: 'embeddings',
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type: 'Embeddings'
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},
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{
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label: 'Base Path to load',
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name: 'basePath',
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description: 'Path to load faiss.index file',
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placeholder: `C:\\Users\\User\\Desktop`,
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type: 'string'
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}
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]
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this.outputs = [
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{
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label: 'Faiss Retriever',
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name: 'retriever',
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baseClasses: this.baseClasses
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},
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{
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label: 'Faiss Vector Store',
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name: 'vectorStore',
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baseClasses: [this.type, ...getBaseClasses(FaissStore)]
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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 embeddings = nodeData.inputs?.embeddings as Embeddings
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const basePath = nodeData.inputs?.basePath as string
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const output = nodeData.outputs?.output as string
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const vectorStore = await FaissStore.load(basePath, embeddings)
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if (output === 'retriever') {
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const retriever = vectorStore.asRetriever()
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return retriever
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} else if (output === 'vectorStore') {
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return vectorStore
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}
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return vectorStore
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}
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}
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module.exports = { nodeClass: Faiss_Existing_VectorStores }
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@@ -1,10 +0,0 @@
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<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-chart-dots-3" 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="M5 7m-2 0a2 2 0 1 0 4 0a2 2 0 1 0 -4 0"></path>
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<path d="M16 15m-2 0a2 2 0 1 0 4 0a2 2 0 1 0 -4 0"></path>
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<path d="M18 6m-3 0a3 3 0 1 0 6 0a3 3 0 1 0 -6 0"></path>
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<path d="M6 18m-3 0a3 3 0 1 0 6 0a3 3 0 1 0 -6 0"></path>
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<path d="M9 17l5 -1.5"></path>
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<path d="M6.5 8.5l7.81 5.37"></path>
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<path d="M7 7l8 -1"></path>
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</svg>
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Before Width: | Height: | Size: 648 B |
@@ -1,85 +0,0 @@
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import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
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import { Embeddings } from 'langchain/embeddings/base'
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import { Document } from 'langchain/document'
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import { getBaseClasses } from '../../../src/utils'
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import { FaissStore } from 'langchain/vectorstores/faiss'
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class FaissUpsert_VectorStores implements INode {
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label: string
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name: string
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description: 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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inputs: INodeParams[]
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outputs: INodeOutputsValue[]
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constructor() {
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this.label = 'Faiss Upsert Document'
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this.name = 'faissUpsert'
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this.type = 'Faiss'
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this.icon = 'faiss.svg'
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this.category = 'Vector Stores'
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this.description = 'Upsert documents to Faiss'
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this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
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this.inputs = [
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{
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label: 'Document',
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name: 'document',
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type: 'Document',
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list: true
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},
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{
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label: 'Embeddings',
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name: 'embeddings',
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type: 'Embeddings'
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},
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{
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label: 'Base Path to store',
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name: 'basePath',
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description: 'Path to store faiss.index file',
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placeholder: `C:\\Users\\User\\Desktop`,
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type: 'string'
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}
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]
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this.outputs = [
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{
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label: 'Faiss Retriever',
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name: 'retriever',
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baseClasses: this.baseClasses
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},
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{
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label: 'Faiss Vector Store',
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name: 'vectorStore',
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baseClasses: [this.type, ...getBaseClasses(FaissStore)]
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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 docs = nodeData.inputs?.document as Document[]
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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const output = nodeData.outputs?.output as string
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const basePath = nodeData.inputs?.basePath as string
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const flattenDocs = docs && docs.length ? docs.flat() : []
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const finalDocs = []
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for (let i = 0; i < flattenDocs.length; i += 1) {
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finalDocs.push(new Document(flattenDocs[i]))
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}
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const vectorStore = await FaissStore.fromDocuments(finalDocs, embeddings)
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await vectorStore.save(basePath)
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if (output === 'retriever') {
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const retriever = vectorStore.asRetriever()
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return retriever
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} else if (output === 'vectorStore') {
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return vectorStore
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}
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return vectorStore
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}
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}
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module.exports = { nodeClass: FaissUpsert_VectorStores }
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@@ -1,10 +0,0 @@
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<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-chart-dots-3" 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="M5 7m-2 0a2 2 0 1 0 4 0a2 2 0 1 0 -4 0"></path>
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<path d="M16 15m-2 0a2 2 0 1 0 4 0a2 2 0 1 0 -4 0"></path>
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<path d="M18 6m-3 0a3 3 0 1 0 6 0a3 3 0 1 0 -6 0"></path>
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<path d="M6 18m-3 0a3 3 0 1 0 6 0a3 3 0 1 0 -6 0"></path>
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<path d="M9 17l5 -1.5"></path>
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<path d="M6.5 8.5l7.81 5.37"></path>
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<path d="M7 7l8 -1"></path>
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</svg>
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Before Width: | Height: | Size: 648 B |
@@ -28,7 +28,6 @@
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"d3-dsv": "2",
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"d3-dsv": "2",
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"dotenv": "^16.0.0",
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"dotenv": "^16.0.0",
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"express": "^4.17.3",
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"express": "^4.17.3",
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"faiss-node": "^0.2.0",
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"form-data": "^4.0.0",
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"form-data": "^4.0.0",
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"graphql": "^16.6.0",
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"graphql": "^16.6.0",
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"langchain": "^0.0.82",
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"langchain": "^0.0.82",
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@@ -34,8 +34,7 @@ import {
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findAvailableConfigs,
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findAvailableConfigs,
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isSameOverrideConfig,
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isSameOverrideConfig,
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replaceAllAPIKeys,
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replaceAllAPIKeys,
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isFlowValidForStream,
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isFlowValidForStream
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isVectorStoreFaiss
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} from './utils'
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} from './utils'
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import { cloneDeep } from 'lodash'
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import { cloneDeep } from 'lodash'
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import { getDataSource } from './DataSource'
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import { getDataSource } from './DataSource'
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@@ -635,8 +634,6 @@ export class App {
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const nodeModule = await import(nodeInstanceFilePath)
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const nodeModule = await import(nodeInstanceFilePath)
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const nodeInstance = new nodeModule.nodeClass()
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const nodeInstance = new nodeModule.nodeClass()
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isStreamValid = isStreamValid && !isVectorStoreFaiss(nodeToExecuteData)
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const result = isStreamValid
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const result = isStreamValid
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? await nodeInstance.run(nodeToExecuteData, incomingInput.question, {
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? await nodeInstance.run(nodeToExecuteData, incomingInput.question, {
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chatHistory: incomingInput.history,
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chatHistory: incomingInput.history,
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@@ -14,7 +14,7 @@ import {
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INodeData,
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INodeData,
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IOverrideConfig
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IOverrideConfig
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} from '../Interface'
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} from '../Interface'
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import { cloneDeep, get, omit, merge } from 'lodash'
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import { cloneDeep, get } from 'lodash'
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import { ICommonObject, getInputVariables } from 'flowise-components'
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import { ICommonObject, getInputVariables } from 'flowise-components'
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import { scryptSync, randomBytes, timingSafeEqual } from 'crypto'
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import { scryptSync, randomBytes, timingSafeEqual } from 'crypto'
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@@ -317,25 +317,6 @@ export const getVariableValue = (paramValue: string, reactFlowNodes: IReactFlowN
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return returnVal
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return returnVal
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}
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}
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/**
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* Temporarily disable streaming if vectorStore is Faiss
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* @param {INodeData} flowNodeData
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* @returns {boolean}
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*/
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export const isVectorStoreFaiss = (flowNodeData: INodeData) => {
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if (flowNodeData.inputs && flowNodeData.inputs.vectorStoreRetriever) {
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const vectorStoreRetriever = flowNodeData.inputs.vectorStoreRetriever
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if (typeof vectorStoreRetriever === 'string' && vectorStoreRetriever.includes('faiss')) return true
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if (
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typeof vectorStoreRetriever === 'object' &&
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vectorStoreRetriever.vectorStore &&
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vectorStoreRetriever.vectorStore.constructor.name === 'FaissStore'
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)
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return true
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}
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return false
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}
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/**
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/**
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* Loop through each inputs and resolve variable if neccessary
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* Loop through each inputs and resolve variable if neccessary
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* @param {INodeData} reactFlowNodeData
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* @param {INodeData} reactFlowNodeData
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@@ -344,12 +325,7 @@ export const isVectorStoreFaiss = (flowNodeData: INodeData) => {
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* @returns {INodeData}
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* @returns {INodeData}
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*/
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*/
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export const resolveVariables = (reactFlowNodeData: INodeData, reactFlowNodes: IReactFlowNode[], question: string): INodeData => {
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export const resolveVariables = (reactFlowNodeData: INodeData, reactFlowNodes: IReactFlowNode[], question: string): INodeData => {
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let flowNodeData = cloneDeep(reactFlowNodeData)
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const flowNodeData = cloneDeep(reactFlowNodeData)
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if (reactFlowNodeData.instance && isVectorStoreFaiss(reactFlowNodeData)) {
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// omit and merge because cloneDeep of instance gives "Illegal invocation" Exception
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const flowNodeDataWithoutInstance = cloneDeep(omit(reactFlowNodeData, ['instance']))
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flowNodeData = merge(flowNodeDataWithoutInstance, { instance: reactFlowNodeData.instance })
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}
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const types = 'inputs'
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const types = 'inputs'
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const getParamValues = (paramsObj: ICommonObject) => {
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const getParamValues = (paramsObj: ICommonObject) => {
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@@ -657,5 +633,5 @@ export const isFlowValidForStream = (reactFlowNodes: IReactFlowNode[], endingNod
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}
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}
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}
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}
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return isChatOrLLMsExist && endingNodeData.category === 'Chains' && !isVectorStoreFaiss(endingNodeData)
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return isChatOrLLMsExist && endingNodeData.category === 'Chains'
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}
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}
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