Merge pull request #27 from FlowiseAI/feature/AutoGPT
Feature/Add AutoGPT, Readfile and Writefile tools
This commit is contained in:
Henry Heng
GitHub
commit
e008718e16
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@ -0,0 +1,97 @@
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import { INode, INodeData, INodeParams } from '../../../src/Interface'
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import { BaseChatModel } from 'langchain/chat_models'
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import { AutoGPT } from 'langchain/experimental/autogpt'
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import { Tool } from 'langchain/tools'
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import { VectorStoreRetriever } from 'langchain/vectorstores/base'
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class AutoGPT_Agents 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 = 'AutoGPT'
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this.name = 'autoGPT'
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this.type = 'AutoGPT'
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this.category = 'Agents'
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this.icon = 'autogpt.png'
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this.description = 'Autonomous agent with chain of thoughts for self-guided task completion'
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this.baseClasses = ['AutoGPT']
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this.inputs = [
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{
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label: 'Allowed Tools',
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name: 'tools',
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type: 'Tool',
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list: true
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},
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{
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label: 'Chat Model',
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name: 'model',
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type: 'BaseChatModel'
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},
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{
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label: 'Vector Store Retriever',
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name: 'vectorStoreRetriever',
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type: 'BaseRetriever'
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},
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{
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label: 'AutoGPT Name',
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name: 'aiName',
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type: 'string',
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placeholder: 'Tom',
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optional: true
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},
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{
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label: 'AutoGPT Role',
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name: 'aiRole',
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type: 'string',
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placeholder: 'Assistant',
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optional: true
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},
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{
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label: 'Maximum Loop',
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name: 'maxLoop',
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type: 'number',
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default: 5,
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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 model = nodeData.inputs?.model as BaseChatModel
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const vectorStoreRetriever = nodeData.inputs?.vectorStoreRetriever as VectorStoreRetriever
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const tools = nodeData.inputs?.tools as Tool[]
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const aiName = (nodeData.inputs?.aiName as string) || 'AutoGPT'
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const aiRole = (nodeData.inputs?.aiRole as string) || 'Assistant'
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const maxLoop = nodeData.inputs?.maxLoop as string
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const autogpt = AutoGPT.fromLLMAndTools(model, tools, {
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memory: vectorStoreRetriever,
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aiName,
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aiRole
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})
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autogpt.maxIterations = parseInt(maxLoop, 10)
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return autogpt
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}
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async run(nodeData: INodeData, input: string): Promise<string> {
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const executor = nodeData.instance as AutoGPT
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try {
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const res = await executor.run([input])
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return res || 'I have completed all my tasks.'
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} catch (e) {
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console.error(e)
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throw new Error(e)
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}
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}
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}
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module.exports = { nodeClass: AutoGPT_Agents }
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After Width: | Height: | Size: 22 KiB |
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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 { ReadFileTool } from 'langchain/tools'
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import { NodeFileStore } from 'langchain/stores/file/node'
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class ReadFile_Tools 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 = 'Read File'
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this.name = 'readFile'
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this.type = 'ReadFile'
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this.icon = 'readfile.svg'
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this.category = 'Tools'
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this.description = 'Read file from disk'
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this.baseClasses = [this.type, 'Tool', ...getBaseClasses(ReadFileTool)]
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this.inputs = [
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{
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label: 'Base Path',
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name: 'basePath',
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placeholder: `C:\\Users\\User\\Desktop`,
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type: 'string',
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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 basePath = nodeData.inputs?.basePath as string
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const store = basePath ? new NodeFileStore(basePath) : new NodeFileStore()
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return new ReadFileTool({ store })
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}
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}
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module.exports = { nodeClass: ReadFile_Tools }
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<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-file-check" 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 3v4a1 1 0 0 0 1 1h4"></path>
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<path d="M17 21h-10a2 2 0 0 1 -2 -2v-14a2 2 0 0 1 2 -2h7l5 5v11a2 2 0 0 1 -2 2z"></path>
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<path d="M9 15l2 2l4 -4"></path>
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</svg>
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After Width: | Height: | Size: 470 B |
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@ -0,0 +1,42 @@
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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 { WriteFileTool } from 'langchain/tools'
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import { NodeFileStore } from 'langchain/stores/file/node'
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class WriteFile_Tools 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 = 'Write File'
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this.name = 'writeFile'
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this.type = 'WriteFile'
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this.icon = 'writefile.svg'
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this.category = 'Tools'
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this.description = 'Write file to disk'
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this.baseClasses = [this.type, 'Tool', ...getBaseClasses(WriteFileTool)]
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this.inputs = [
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{
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label: 'Base Path',
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name: 'basePath',
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placeholder: `C:\\Users\\User\\Desktop`,
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type: 'string',
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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 basePath = nodeData.inputs?.basePath as string
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const store = basePath ? new NodeFileStore(basePath) : new NodeFileStore()
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return new WriteFileTool({ store })
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}
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}
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module.exports = { nodeClass: WriteFile_Tools }
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<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-file-pencil" 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 3v4a1 1 0 0 0 1 1h4"></path>
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<path d="M17 21h-10a2 2 0 0 1 -2 -2v-14a2 2 0 0 1 2 -2h7l5 5v11a2 2 0 0 1 -2 2z"></path>
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<path d="M10 18l5 -5a1.414 1.414 0 0 0 -2 -2l-5 5v2h2z"></path>
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</svg>
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After Width: | Height: | Size: 502 B |
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@ -21,7 +21,7 @@ class Chroma_Existing_VectorStores implements INode {
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this.icon = 'chroma.svg'
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this.icon = 'chroma.svg'
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this.category = 'Vector Stores'
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this.category = 'Vector Stores'
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this.description = 'Load existing index from Chroma (i.e: Document has been upserted)'
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this.description = 'Load existing index from Chroma (i.e: Document has been upserted)'
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this.baseClasses = [this.type, 'BaseRetriever']
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this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
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this.inputs = [
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this.inputs = [
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{
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{
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label: 'Embeddings',
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label: 'Embeddings',
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@ -38,7 +38,7 @@ class Chroma_Existing_VectorStores implements INode {
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{
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{
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label: 'Chroma Retriever',
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label: 'Chroma Retriever',
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name: 'retriever',
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name: 'retriever',
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baseClasses: [this.type, 'BaseRetriever']
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baseClasses: this.baseClasses
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},
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},
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{
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{
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label: 'Chroma Vector Store',
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label: 'Chroma Vector Store',
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@ -22,7 +22,7 @@ class ChromaUpsert_VectorStores implements INode {
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this.icon = 'chroma.svg'
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this.icon = 'chroma.svg'
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this.category = 'Vector Stores'
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this.category = 'Vector Stores'
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this.description = 'Upsert documents to Chroma'
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this.description = 'Upsert documents to Chroma'
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this.baseClasses = [this.type, 'BaseRetriever']
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this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
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this.inputs = [
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this.inputs = [
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{
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{
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label: 'Document',
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label: 'Document',
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@ -44,7 +44,7 @@ class ChromaUpsert_VectorStores implements INode {
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{
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{
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label: 'Chroma Retriever',
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label: 'Chroma Retriever',
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name: 'retriever',
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name: 'retriever',
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baseClasses: [this.type, 'BaseRetriever']
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baseClasses: this.baseClasses
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},
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},
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{
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{
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label: 'Chroma Vector Store',
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label: 'Chroma Vector Store',
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@ -22,7 +22,7 @@ class Pinecone_Existing_VectorStores implements INode {
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this.icon = 'pinecone.png'
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this.icon = 'pinecone.png'
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this.category = 'Vector Stores'
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this.category = 'Vector Stores'
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this.description = 'Load existing index from Pinecone (i.e: Document has been upserted)'
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this.description = 'Load existing index from Pinecone (i.e: Document has been upserted)'
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this.baseClasses = [this.type, 'BaseRetriever']
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this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
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this.inputs = [
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this.inputs = [
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{
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{
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label: 'Embeddings',
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label: 'Embeddings',
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@ -49,7 +49,7 @@ class Pinecone_Existing_VectorStores implements INode {
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{
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{
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label: 'Pinecone Retriever',
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label: 'Pinecone Retriever',
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name: 'retriever',
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name: 'retriever',
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baseClasses: [this.type, 'BaseRetriever']
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baseClasses: this.baseClasses
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},
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},
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{
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{
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label: 'Pinecone Vector Store',
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label: 'Pinecone Vector Store',
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@ -23,7 +23,7 @@ class PineconeUpsert_VectorStores implements INode {
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this.icon = 'pinecone.png'
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this.icon = 'pinecone.png'
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this.category = 'Vector Stores'
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this.category = 'Vector Stores'
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this.description = 'Upsert documents to Pinecone'
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this.description = 'Upsert documents to Pinecone'
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this.baseClasses = [this.type, 'BaseRetriever']
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this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
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this.inputs = [
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this.inputs = [
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{
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{
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label: 'Document',
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label: 'Document',
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@ -55,7 +55,7 @@ class PineconeUpsert_VectorStores implements INode {
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{
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{
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label: 'Pinecone Retriever',
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label: 'Pinecone Retriever',
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name: 'retriever',
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name: 'retriever',
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baseClasses: [this.type, 'BaseRetriever']
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baseClasses: this.baseClasses
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},
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},
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{
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{
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label: 'Pinecone Vector Store',
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label: 'Pinecone Vector Store',
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@ -27,7 +27,7 @@
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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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"form-data": "^4.0.0",
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"form-data": "^4.0.0",
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"langchain": "^0.0.59",
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"langchain": "^0.0.60",
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"moment": "^2.29.3",
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"moment": "^2.29.3",
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"node-fetch": "2",
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"node-fetch": "2",
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"pdf-parse": "^1.1.1",
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"pdf-parse": "^1.1.1",
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@ -0,0 +1,521 @@
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{
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"description": "Use AutoGPT - Autonomous agent with chain of thoughts for self-guided task completion",
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"nodes": [
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{
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"width": 300,
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"height": 552,
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"id": "pineconeExistingIndex_0",
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"position": {
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"x": 901.718945246004,
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"y": 444.1940851368503
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},
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"type": "customNode",
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"data": {
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"id": "pineconeExistingIndex_0",
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"label": "Pinecone Load Existing Index",
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"name": "pineconeExistingIndex",
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"type": "Pinecone",
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"baseClasses": ["Pinecone", "VectorStoreRetriever", "BaseRetriever"],
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"category": "Vector Stores",
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"description": "Load existing index from Pinecone (i.e: Document has been upserted)",
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"inputParams": [
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{
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"label": "Pinecone Api Key",
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"name": "pineconeApiKey",
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||||||
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"type": "password",
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||||||
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"id": "pineconeExistingIndex_0-input-pineconeApiKey-password"
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||||||
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},
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{
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||||||
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"label": "Pinecone Environment",
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||||||
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"name": "pineconeEnv",
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||||||
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"type": "string",
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||||||
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"id": "pineconeExistingIndex_0-input-pineconeEnv-string"
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||||||
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},
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{
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||||||
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"label": "Pinecone Index",
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||||||
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"name": "pineconeIndex",
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"type": "string",
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||||||
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"id": "pineconeExistingIndex_0-input-pineconeIndex-string"
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||||||
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}
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||||||
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],
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"inputAnchors": [
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{
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||||||
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"label": "Embeddings",
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||||||
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"name": "embeddings",
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||||||
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"type": "Embeddings",
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||||||
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"id": "pineconeExistingIndex_0-input-embeddings-Embeddings"
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||||||
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}
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||||||
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],
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"inputs": {
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"embeddings": "{{openAIEmbeddings_0.data.instance}}",
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||||||
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"pineconeEnv": "us-west4-gcp",
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||||||
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"pineconeIndex": "test"
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||||||
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},
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||||||
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"outputAnchors": [
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||||||
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{
|
||||||
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"name": "output",
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||||||
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"label": "Output",
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||||||
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"type": "options",
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||||||
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"options": [
|
||||||
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{
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||||||
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"id": "pineconeExistingIndex_0-output-retriever-Pinecone|VectorStoreRetriever|BaseRetriever",
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||||||
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"name": "retriever",
|
||||||
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"label": "Pinecone Retriever",
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||||||
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"type": "Pinecone | VectorStoreRetriever | BaseRetriever"
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||||||
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},
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||||||
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{
|
||||||
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"id": "pineconeExistingIndex_0-output-vectorStore-Pinecone|VectorStore",
|
||||||
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"name": "vectorStore",
|
||||||
|
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
|
"id": "serpAPI_0-serpAPI_0-output-serpAPI-SerpAPI|Tool|StructuredTool|BaseLangChain-autoGPT_0-autoGPT_0-input-tools-Tool",
|
||||||
|
"data": {
|
||||||
|
"label": ""
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"source": "readFile_0",
|
||||||
|
"sourceHandle": "readFile_0-output-readFile-ReadFile|Tool|StructuredTool|BaseLangChain",
|
||||||
|
"target": "autoGPT_0",
|
||||||
|
"targetHandle": "autoGPT_0-input-tools-Tool",
|
||||||
|
"type": "buttonedge",
|
||||||
|
"id": "readFile_0-readFile_0-output-readFile-ReadFile|Tool|StructuredTool|BaseLangChain-autoGPT_0-autoGPT_0-input-tools-Tool",
|
||||||
|
"data": {
|
||||||
|
"label": ""
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"source": "writeFile_0",
|
||||||
|
"sourceHandle": "writeFile_0-output-writeFile-WriteFile|Tool|StructuredTool|BaseLangChain",
|
||||||
|
"target": "autoGPT_0",
|
||||||
|
"targetHandle": "autoGPT_0-input-tools-Tool",
|
||||||
|
"type": "buttonedge",
|
||||||
|
"id": "writeFile_0-writeFile_0-output-writeFile-WriteFile|Tool|StructuredTool|BaseLangChain-autoGPT_0-autoGPT_0-input-tools-Tool",
|
||||||
|
"data": {
|
||||||
|
"label": ""
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"source": "chatOpenAI_0",
|
||||||
|
"sourceHandle": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|BaseLangChain",
|
||||||
|
"target": "autoGPT_0",
|
||||||
|
"targetHandle": "autoGPT_0-input-model-BaseChatModel",
|
||||||
|
"type": "buttonedge",
|
||||||
|
"id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|BaseLangChain-autoGPT_0-autoGPT_0-input-model-BaseChatModel",
|
||||||
|
"data": {
|
||||||
|
"label": ""
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"source": "pineconeExistingIndex_0",
|
||||||
|
"sourceHandle": "pineconeExistingIndex_0-output-retriever-Pinecone|VectorStoreRetriever|BaseRetriever",
|
||||||
|
"target": "autoGPT_0",
|
||||||
|
"targetHandle": "autoGPT_0-input-vectorStoreRetriever-BaseRetriever",
|
||||||
|
"type": "buttonedge",
|
||||||
|
"id": "pineconeExistingIndex_0-pineconeExistingIndex_0-output-retriever-Pinecone|VectorStoreRetriever|BaseRetriever-autoGPT_0-autoGPT_0-input-vectorStoreRetriever-BaseRetriever",
|
||||||
|
"data": {
|
||||||
|
"label": ""
|
||||||
|
}
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
|
@ -292,9 +292,9 @@ export const rearrangeToolsOrdering = (newValues, sourceNodeId) => {
|
||||||
newValues.push(`{{${sourceNodeId}.data.instance}}`)
|
newValues.push(`{{${sourceNodeId}.data.instance}}`)
|
||||||
|
|
||||||
const sortKey = (item) => {
|
const sortKey = (item) => {
|
||||||
if (item.includes('requestsGet')) {
|
if (item.includes('requestsGet') || item.includes('readFile')) {
|
||||||
return 0
|
return 0
|
||||||
} else if (item.includes('requestsPost')) {
|
} else if (item.includes('requestsPost') || item.includes('writeFile')) {
|
||||||
return 1
|
return 1
|
||||||
} else {
|
} else {
|
||||||
return 2
|
return 2
|
||||||
|
|
|
||||||
Loading…
Reference in New Issue