mirror of
https://github.com/farcasclaudiu/Flowise.git
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Merge branch 'main' into feature/ChatGPT-Plugin
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@@ -0,0 +1,81 @@
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import { INode, INodeData, INodeParams } from '../../../src/Interface'
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import { SqlDatabaseChain } from 'langchain/chains'
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import { getBaseClasses } from '../../../src/utils'
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import { DataSource } from 'typeorm'
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import { SqlDatabase } from 'langchain/sql_db'
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import { BaseLLM } from 'langchain/llms/base'
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class SqlDatabaseChain_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 = 'Sql Database Chain'
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this.name = 'sqlDatabaseChain'
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this.type = 'SqlDatabaseChain'
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this.icon = 'sqlchain.svg'
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this.category = 'Chains'
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this.description = 'Answer questions over a SQL database'
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this.baseClasses = [this.type, ...getBaseClasses(SqlDatabaseChain)]
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this.inputs = [
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{
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label: 'LLM',
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name: 'llm',
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type: 'BaseLLM'
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},
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{
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label: 'Database',
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name: 'database',
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type: 'options',
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options: [
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{
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label: 'SQlite',
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name: 'sqlite'
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}
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],
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default: 'sqlite'
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},
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{
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label: 'Database File Path',
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name: 'dbFilePath',
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type: 'string',
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placeholder: 'C:/Users/chinook.db'
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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 databaseType = nodeData.inputs?.database
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const llm = nodeData.inputs?.llm as BaseLLM
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const dbFilePath = nodeData.inputs?.dbFilePath
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const datasource = new DataSource({
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type: databaseType,
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database: dbFilePath
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})
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const db = await SqlDatabase.fromDataSourceParams({
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appDataSource: datasource
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})
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const chain = new SqlDatabaseChain({
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llm,
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database: db
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})
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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 SqlDatabaseChain
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const res = await chain.run(input)
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return res
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}
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}
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module.exports = { nodeClass: SqlDatabaseChain_Chains }
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@@ -0,0 +1,7 @@
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<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-sql" 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="M12 8a2 2 0 0 1 2 2v4a2 2 0 1 1 -4 0v-4a2 2 0 0 1 2 -2z"></path>
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<path d="M17 8v8h4"></path>
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<path d="M13 15l1 1"></path>
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<path d="M3 15a1 1 0 0 0 1 1h2a1 1 0 0 0 1 -1v-2a1 1 0 0 0 -1 -1h-2a1 1 0 0 1 -1 -1v-2a1 1 0 0 1 1 -1h2a1 1 0 0 1 1 1"></path>
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</svg>
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After Width: | Height: | Size: 560 B |
@@ -0,0 +1,64 @@
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import { INode, INodeData, INodeParams } from '../../../src/Interface'
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import { TextSplitter } from 'langchain/text_splitter'
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import { CheerioWebBaseLoader } from 'langchain/document_loaders/web/cheerio'
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class Cheerio_DocumentLoaders 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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constructor() {
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this.label = 'Cheerio Web Scraper'
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this.name = 'cheerioWebScraper'
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this.type = 'Document'
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this.icon = 'cheerio.svg'
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this.category = 'Document Loaders'
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this.description = `Load data from webpages`
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this.baseClasses = [this.type]
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this.inputs = [
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{
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label: 'URL',
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name: 'url',
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type: 'string'
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},
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{
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label: 'Text Splitter',
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name: 'textSplitter',
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type: 'TextSplitter',
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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 textSplitter = nodeData.inputs?.textSplitter as TextSplitter
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let url = nodeData.inputs?.url as string
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var urlPattern = new RegExp(
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'^(https?:\\/\\/)?' + // validate protocol
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'((([a-z\\d]([a-z\\d-]*[a-z\\d])*)\\.)+[a-z]{2,}|' + // validate domain name
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'((\\d{1,3}\\.){3}\\d{1,3}))' + // validate OR ip (v4) address
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'(\\:\\d+)?(\\/[-a-z\\d%_.~+]*)*' + // validate port and path
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'(\\?[;&a-z\\d%_.~+=-]*)?' + // validate query string
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'(\\#[-a-z\\d_]*)?$',
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'i'
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) // validate fragment locator
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const loader = new CheerioWebBaseLoader(urlPattern.test(url.trim()) ? url.trim() : '')
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if (textSplitter) {
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const docs = await loader.loadAndSplit(textSplitter)
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return docs
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} else {
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const docs = await loader.load()
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return docs
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}
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}
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}
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module.exports = { nodeClass: Cheerio_DocumentLoaders }
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@@ -0,0 +1,5 @@
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<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-circle-letter-c" 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="M12 12m-9 0a9 9 0 1 0 18 0a9 9 0 1 0 -18 0"></path>
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<path d="M14 10a2 2 0 1 0 -4 0v4a2 2 0 1 0 4 0"></path>
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</svg>
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After Width: | Height: | Size: 425 B |
@@ -0,0 +1,40 @@
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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 { CohereEmbeddings } from 'langchain/embeddings/cohere'
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class CohereEmbedding_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 = 'Cohere Embeddings'
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this.name = 'cohereEmbeddings'
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this.type = 'CohereEmbeddings'
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this.icon = 'cohere.png'
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this.category = 'Embeddings'
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this.description = 'Cohere API to generate embeddings for a given text'
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this.baseClasses = [this.type, ...getBaseClasses(CohereEmbeddings)]
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this.inputs = [
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{
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label: 'Cohere API Key',
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name: 'cohereApiKey',
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type: 'password'
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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?.cohereApiKey as string
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const model = new CohereEmbeddings({ apiKey })
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return model
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}
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}
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module.exports = { nodeClass: CohereEmbedding_Embeddings }
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