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https://github.com/farcasclaudiu/Flowise.git
synced 2026-06-28 07:00:49 +03:00
Feature/lang graph (#2319)
* add langgraph * datasource: initial commit * datasource: datasource details and chunks * datasource: Document Store Node * more changes * Document Store - Base functionality * Document Store Loader Component * Document Store Loader Component * before merging the modularity PR * after merging the modularity PR * preview mode * initial draft PR * fixes * minor updates and fixes * preview with loader and splitter * preview with credential * show stored chunks * preview update... * edit config * save, preview and other changes * save, preview and other changes * save, process and other changes * save, process and other changes * alpha1 - for internal testing * rerouting urls * bug fix on new leader create * pagination support for chunks * delete document store * Update pnpm-lock.yaml * doc store card view * Update store files to use updated storage functions, Document Store Table View and other changes * ui changes * add expanded chunk dialog, improve ui * change throw Error to InternalError * Bug Fixes and removal of subFolder, adding of view chunks for store * lint fixes * merge changes * DocumentStoreStatus component * ui changes for doc store * add remove metadata key field, add custom document loader * add chatflows used doc store chips * add types/interfaces to DocumentStore Services * document loader list dialog title bar color change * update interfaces * Whereused Chatflow Name and Added chunkNo to retain order of created chunks. * use typeorm order chunkNo, ui changes * update tabler icons react * cleanup agents * add pysandbox tool * add abort functionality, loading next agent * add empty view svg * update chatflow tool with chatId * rename to agentflows * update worker for prompt input values * update dashboard to agentflows, agentcanvas * fix marketplace use template * add agentflow templates * resolve merge conflict * update baseURL --------- Co-authored-by: vinodkiran <vinodkiran@usa.net> Co-authored-by: Vinod Paidimarry <vinodkiran@outlook.in>
This commit is contained in:
Henry Heng
@@ -0,0 +1,345 @@
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import {
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ICommonObject,
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IMultiAgentNode,
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IAgentReasoning,
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ITeamState,
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ConsoleCallbackHandler,
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additionalCallbacks
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} from 'flowise-components'
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import { IChatFlow, IComponentNodes, IDepthQueue, IReactFlowNode, IReactFlowObject } from '../Interface'
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import { Server } from 'socket.io'
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import { buildFlow, getStartingNodes, getEndingNodes, constructGraphs, databaseEntities } from '../utils'
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import { getRunningExpressApp } from './getRunningExpressApp'
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import logger from './logger'
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import { StateGraph, END } from '@langchain/langgraph'
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import { BaseMessage, HumanMessage } from '@langchain/core/messages'
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import { cloneDeep, flatten } from 'lodash'
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import { replaceInputsWithConfig, resolveVariables } from '.'
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import { StatusCodes } from 'http-status-codes'
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import { InternalFlowiseError } from '../errors/internalFlowiseError'
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import { getErrorMessage } from '../errors/utils'
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/**
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* Build Agent Graph
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* @param {IChatFlow} chatflow
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* @param {string} chatId
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* @param {string} sessionId
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* @param {ICommonObject} incomingInput
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* @param {string} baseURL
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* @param {Server} socketIO
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*/
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export const buildAgentGraph = async (
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chatflow: IChatFlow,
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chatId: string,
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sessionId: string,
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incomingInput: ICommonObject,
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baseURL?: string,
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socketIO?: Server
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): Promise<any> => {
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try {
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const appServer = getRunningExpressApp()
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const chatflowid = chatflow.id
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/*** Get chatflows and prepare data ***/
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const flowData = chatflow.flowData
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const parsedFlowData: IReactFlowObject = JSON.parse(flowData)
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const nodes = parsedFlowData.nodes
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const edges = parsedFlowData.edges
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/*** Get Ending Node with Directed Graph ***/
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const { graph, nodeDependencies } = constructGraphs(nodes, edges)
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const directedGraph = graph
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const endingNodes = getEndingNodes(nodeDependencies, directedGraph, nodes)
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/*** Get Starting Nodes with Reversed Graph ***/
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const constructedObj = constructGraphs(nodes, edges, { isReversed: true })
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const nonDirectedGraph = constructedObj.graph
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let startingNodeIds: string[] = []
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let depthQueue: IDepthQueue = {}
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const endingNodeIds = endingNodes.map((n) => n.id)
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for (const endingNodeId of endingNodeIds) {
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const resx = getStartingNodes(nonDirectedGraph, endingNodeId)
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startingNodeIds.push(...resx.startingNodeIds)
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depthQueue = Object.assign(depthQueue, resx.depthQueue)
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}
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startingNodeIds = [...new Set(startingNodeIds)]
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// Initialize nodes like ChatModels, Tools, etc.
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const reactFlowNodes = await buildFlow(
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startingNodeIds,
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nodes,
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edges,
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graph,
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depthQueue,
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appServer.nodesPool.componentNodes,
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incomingInput.question,
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[],
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chatId,
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sessionId,
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chatflowid,
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appServer.AppDataSource,
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incomingInput?.overrideConfig,
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appServer.cachePool,
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false,
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undefined,
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incomingInput.uploads,
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baseURL
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)
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const options = {
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chatId,
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sessionId,
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chatflowid,
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logger,
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analytic: chatflow.analytic,
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appDataSource: appServer.AppDataSource,
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databaseEntities: databaseEntities,
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cachePool: appServer.cachePool,
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uploads: incomingInput.uploads,
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baseURL,
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signal: new AbortController()
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}
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let streamResults
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let finalResult = ''
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let agentReasoning: IAgentReasoning[] = []
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const workerNodes: IReactFlowNode[] = reactFlowNodes.filter((node: IReactFlowNode) => node.data.name === 'worker')
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const supervisorNodes: IReactFlowNode[] = reactFlowNodes.filter((node: IReactFlowNode) => node.data.name === 'supervisor')
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const mapNameToLabel: Record<string, string> = {}
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for (const node of [...workerNodes, ...supervisorNodes]) {
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mapNameToLabel[node.data.instance.name] = node.data.instance.label
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}
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try {
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streamResults = await compileGraph(
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chatflow,
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mapNameToLabel,
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reactFlowNodes,
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endingNodeIds,
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appServer.nodesPool.componentNodes,
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options,
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startingNodeIds,
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incomingInput.question,
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incomingInput?.overrideConfig
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)
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if (streamResults) {
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let isStreamingStarted = false
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for await (const output of await streamResults) {
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if (!output?.__end__) {
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const agentName = Object.keys(output)[0]
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const usedTools = output[agentName]?.messages
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? output[agentName].messages.map((msg: any) => msg.additional_kwargs?.usedTools)
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: []
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const sourceDocuments = output[agentName]?.messages
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? output[agentName].messages.map((msg: any) => msg.additional_kwargs?.sourceDocuments)
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: []
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const messages = output[agentName]?.messages ? output[agentName].messages.map((msg: any) => msg.content) : []
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const reasoning = {
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agentName: mapNameToLabel[agentName],
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messages,
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next: output[agentName]?.next,
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instructions: output[agentName]?.instructions,
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usedTools: flatten(usedTools),
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sourceDocuments: flatten(sourceDocuments)
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}
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agentReasoning.push(reasoning)
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if (socketIO && incomingInput.socketIOClientId) {
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if (!isStreamingStarted) {
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isStreamingStarted = true
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socketIO.to(incomingInput.socketIOClientId).emit('start', JSON.stringify(agentReasoning))
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}
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socketIO.to(incomingInput.socketIOClientId).emit('agentReasoning', JSON.stringify(agentReasoning))
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// Send loading next agent indicator
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if (reasoning.next && reasoning.next !== 'FINISH' && reasoning.next !== 'END') {
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socketIO
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.to(incomingInput.socketIOClientId)
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.emit('nextAgent', mapNameToLabel[reasoning.next] || reasoning.next)
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}
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}
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} else {
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finalResult = output.__end__.messages.length ? output.__end__.messages.pop()?.content : ''
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if (Array.isArray(finalResult)) finalResult = output.__end__.instructions
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if (finalResult === incomingInput.question) {
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const supervisorNode = reactFlowNodes.find((node: IReactFlowNode) => node.data.name === 'supervisor')
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const llm = supervisorNode?.data?.instance?.llm
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if (llm) {
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const res = await llm.invoke(incomingInput.question)
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finalResult = res?.content
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}
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}
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if (socketIO && incomingInput.socketIOClientId) {
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socketIO.to(incomingInput.socketIOClientId).emit('token', finalResult)
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}
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}
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}
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return { finalResult, agentReasoning }
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}
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} catch (e) {
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if (socketIO && incomingInput.socketIOClientId) {
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socketIO.to(incomingInput.socketIOClientId).emit('abort')
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}
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return { finalResult, agentReasoning }
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}
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return streamResults
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} catch (e) {
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logger.error('[server]: Error:', e)
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throw new InternalFlowiseError(StatusCodes.INTERNAL_SERVER_ERROR, `Error buildAgentGraph - ${getErrorMessage(e)}`)
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}
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}
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/**
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* Compile Graph
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* @param {IChatFlow} chatflow
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* @param {Record<string, string>} mapNameToLabel
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* @param {IReactFlowNode[]} reactflowNodes
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* @param {string[]} workerNodeIds
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* @param {IComponentNodes} componentNodes
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* @param {ICommonObject} options
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* @param {string[]} startingNodeIds
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* @param {string} question
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* @param {ICommonObject} overrideConfig
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*/
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const compileGraph = async (
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chatflow: IChatFlow,
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mapNameToLabel: Record<string, string>,
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reactflowNodes: IReactFlowNode[] = [],
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workerNodeIds: string[],
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componentNodes: IComponentNodes,
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options: ICommonObject,
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startingNodeIds: string[],
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question: string,
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overrideConfig?: ICommonObject
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) => {
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const appServer = getRunningExpressApp()
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const channels: ITeamState = {
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messages: {
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value: (x: BaseMessage[], y: BaseMessage[]) => x.concat(y),
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default: () => []
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},
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next: 'initialState',
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instructions: "Solve the user's request.",
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team_members: []
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}
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const workflowGraph = new StateGraph<ITeamState>({
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//@ts-ignore
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channels
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})
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const workerNodes = reactflowNodes.filter((node) => workerNodeIds.includes(node.data.id))
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let supervisorWorkers: { [key: string]: IMultiAgentNode[] } = {}
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// Init worker nodes
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for (const workerNode of workerNodes) {
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const nodeInstanceFilePath = componentNodes[workerNode.data.name].filePath as string
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const nodeModule = await import(nodeInstanceFilePath)
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const newNodeInstance = new nodeModule.nodeClass()
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let flowNodeData = cloneDeep(workerNode.data)
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if (overrideConfig) flowNodeData = replaceInputsWithConfig(flowNodeData, overrideConfig)
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flowNodeData = resolveVariables(flowNodeData, reactflowNodes, question, [])
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try {
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const workerResult: IMultiAgentNode = await newNodeInstance.init(flowNodeData, question, options)
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const parentSupervisor = workerResult.parentSupervisorName
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if (!parentSupervisor || workerResult.type !== 'worker') continue
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if (Object.prototype.hasOwnProperty.call(supervisorWorkers, parentSupervisor)) {
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supervisorWorkers[parentSupervisor].push(workerResult)
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} else {
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supervisorWorkers[parentSupervisor] = [workerResult]
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}
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workflowGraph.addNode(workerResult.name, workerResult.node)
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} catch (e) {
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throw new InternalFlowiseError(StatusCodes.INTERNAL_SERVER_ERROR, `Error initialize worker nodes - ${getErrorMessage(e)}`)
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}
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}
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// Init supervisor nodes
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for (const supervisor in supervisorWorkers) {
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const supervisorInputLabel = mapNameToLabel[supervisor]
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const supervisorNode = reactflowNodes.find((node) => supervisorInputLabel === node.data.inputs?.supervisorName)
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if (!supervisorNode) continue
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const nodeInstanceFilePath = componentNodes[supervisorNode.data.name].filePath as string
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const nodeModule = await import(nodeInstanceFilePath)
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const newNodeInstance = new nodeModule.nodeClass()
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let flowNodeData = cloneDeep(supervisorNode.data)
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if (overrideConfig) flowNodeData = replaceInputsWithConfig(flowNodeData, overrideConfig)
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flowNodeData = resolveVariables(flowNodeData, reactflowNodes, question, [])
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if (flowNodeData.inputs) flowNodeData.inputs.workerNodes = supervisorWorkers[supervisor]
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try {
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const supervisorResult: IMultiAgentNode = await newNodeInstance.init(flowNodeData, question, options)
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if (!supervisorResult.workers?.length) continue
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if (supervisorResult.moderations && supervisorResult.moderations.length > 0) {
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try {
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for (const moderation of supervisorResult.moderations) {
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question = await moderation.checkForViolations(question)
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}
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} catch (e) {
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throw new InternalFlowiseError(StatusCodes.INTERNAL_SERVER_ERROR, getErrorMessage(e))
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}
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}
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workflowGraph.addNode(supervisorResult.name, supervisorResult.node)
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for (const worker of supervisorResult.workers) {
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workflowGraph.addEdge(worker, supervisorResult.name)
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}
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let conditionalEdges: { [key: string]: string } = {}
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for (let i = 0; i < supervisorResult.workers.length; i++) {
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conditionalEdges[supervisorResult.workers[i]] = supervisorResult.workers[i]
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}
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workflowGraph.addConditionalEdges(supervisorResult.name, (x: ITeamState) => x.next, {
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...conditionalEdges,
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FINISH: END
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})
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workflowGraph.setEntryPoint(supervisorResult.name)
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// Add agentflow to pool
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;(workflowGraph as any).signal = options.signal
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appServer.chatflowPool.add(
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`${chatflow.id}_${options.chatId}`,
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workflowGraph as any,
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reactflowNodes.filter((node) => startingNodeIds.includes(node.id)),
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overrideConfig
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)
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// TODO: add persistence
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// const memory = new MemorySaver()
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const graph = workflowGraph.compile()
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const loggerHandler = new ConsoleCallbackHandler(logger)
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const callbacks = await additionalCallbacks(flowNodeData, options)
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// Return stream result as we should only have 1 supervisor
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return await graph.stream(
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{
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messages: [new HumanMessage({ content: question })]
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},
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{ recursionLimit: supervisorResult?.recursionLimit ?? 100, callbacks: [loggerHandler, ...callbacks] }
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)
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} catch (e) {
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throw new InternalFlowiseError(StatusCodes.INTERNAL_SERVER_ERROR, `Error initialize supervisor nodes - ${getErrorMessage(e)}`)
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}
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}
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}
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