import { IMessage, IDatabaseEntity, INode, INodeData, INodeParams, MemoryMethods, ICommonObject, FlowiseSummaryBufferMemory } from '../../../src/Interface' import { getBaseClasses, mapChatMessageToBaseMessage } from '../../../src/utils' import { BaseLanguageModel } from '@langchain/core/language_models/base' import { BaseMessage, getBufferString, HumanMessage } from '@langchain/core/messages' import { ConversationSummaryBufferMemory, ConversationSummaryBufferMemoryInput } from 'langchain/memory' import { DataSource } from 'typeorm' import { ChatAnthropic } from '../../chatmodels/ChatAnthropic/FlowiseChatAnthropic' class ConversationSummaryBufferMemory_Memory implements INode { label: string name: string version: number description: string type: string icon: string category: string baseClasses: string[] inputs: INodeParams[] constructor() { this.label = 'Conversation Summary Buffer Memory' this.name = 'conversationSummaryBufferMemory' this.version = 1.0 this.type = 'ConversationSummaryBufferMemory' this.icon = 'memory.svg' this.category = 'Memory' this.description = 'Uses token length to decide when to summarize conversations' this.baseClasses = [this.type, ...getBaseClasses(ConversationSummaryBufferMemory)] this.inputs = [ { label: 'Chat Model', name: 'model', type: 'BaseChatModel' }, { label: 'Max Token Limit', name: 'maxTokenLimit', type: 'number', default: 2000, description: 'Summarize conversations once token limit is reached. Default to 2000' }, { label: 'Session Id', name: 'sessionId', type: 'string', description: 'If not specified, a random id will be used. Learn more', default: '', optional: true, additionalParams: true }, { label: 'Memory Key', name: 'memoryKey', type: 'string', default: 'chat_history', additionalParams: true } ] } async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { const model = nodeData.inputs?.model as BaseLanguageModel const _maxTokenLimit = nodeData.inputs?.maxTokenLimit as string const maxTokenLimit = _maxTokenLimit ? parseInt(_maxTokenLimit, 10) : 2000 const sessionId = nodeData.inputs?.sessionId as string const memoryKey = (nodeData.inputs?.memoryKey as string) ?? 'chat_history' const appDataSource = options.appDataSource as DataSource const databaseEntities = options.databaseEntities as IDatabaseEntity const chatflowid = options.chatflowid as string const orgId = options.orgId as string const obj: ConversationSummaryBufferMemoryInput & BufferMemoryExtendedInput = { llm: model, sessionId, memoryKey, maxTokenLimit, returnMessages: true, appDataSource, databaseEntities, chatflowid, orgId } return new ConversationSummaryBufferMemoryExtended(obj) } } interface BufferMemoryExtendedInput { sessionId: string appDataSource: DataSource databaseEntities: IDatabaseEntity chatflowid: string orgId: string } class ConversationSummaryBufferMemoryExtended extends FlowiseSummaryBufferMemory implements MemoryMethods { appDataSource: DataSource databaseEntities: IDatabaseEntity chatflowid: string orgId: string sessionId = '' constructor(fields: ConversationSummaryBufferMemoryInput & BufferMemoryExtendedInput) { super(fields) this.sessionId = fields.sessionId this.appDataSource = fields.appDataSource this.databaseEntities = fields.databaseEntities this.chatflowid = fields.chatflowid this.orgId = fields.orgId } async getChatMessages( overrideSessionId = '', returnBaseMessages = false, prependMessages?: IMessage[] ): Promise { const id = overrideSessionId ? overrideSessionId : this.sessionId if (!id) return [] let chatMessage = await this.appDataSource.getRepository(this.databaseEntities['ChatMessage']).find({ where: { sessionId: id, chatflowid: this.chatflowid }, order: { createdDate: 'ASC' } }) if (prependMessages?.length) { chatMessage.unshift(...prependMessages) } let baseMessages = await mapChatMessageToBaseMessage(chatMessage, this.orgId) // Prune baseMessages if it exceeds max token limit if (this.movingSummaryBuffer) { baseMessages = [new this.summaryChatMessageClass(this.movingSummaryBuffer), ...baseMessages] } let currBufferLength = 0 if (this.llm && typeof this.llm !== 'string') { currBufferLength = await this.llm.getNumTokens(getBufferString(baseMessages, this.humanPrefix, this.aiPrefix)) if (currBufferLength > this.maxTokenLimit) { const prunedMemory = [] while (currBufferLength > this.maxTokenLimit) { const poppedMessage = baseMessages.shift() if (poppedMessage) { prunedMemory.push(poppedMessage) currBufferLength = await this.llm.getNumTokens(getBufferString(baseMessages, this.humanPrefix, this.aiPrefix)) } } this.movingSummaryBuffer = await this.predictNewSummary(prunedMemory, this.movingSummaryBuffer) } } // ----------- Finished Pruning --------------- if (this.movingSummaryBuffer) { // Anthropic doesn't support multiple system messages if (this.llm instanceof ChatAnthropic) { baseMessages = [new HumanMessage(`Below is the summarized conversation:\n\n${this.movingSummaryBuffer}`), ...baseMessages] } else { baseMessages = [new this.summaryChatMessageClass(this.movingSummaryBuffer), ...baseMessages] } } if (returnBaseMessages) { return baseMessages } let returnIMessages: IMessage[] = [] for (const m of baseMessages) { returnIMessages.push({ message: m.content as string, type: m._getType() === 'human' ? 'userMessage' : 'apiMessage' }) } return returnIMessages } async addChatMessages(): Promise { // adding chat messages is done on server level return } async clearChatMessages(): Promise { // clearing chat messages is done on server level return } } module.exports = { nodeClass: ConversationSummaryBufferMemory_Memory }