import { BaseLanguageModel } from '@langchain/core/language_models/base' import { MultiPromptChain } from 'langchain/chains' import { ICommonObject, INode, INodeData, INodeParams, IServerSideEventStreamer, PromptRetriever } from '../../../src/Interface' import { getBaseClasses } from '../../../src/utils' import { ConsoleCallbackHandler, CustomChainHandler, additionalCallbacks } from '../../../src/handler' import { checkInputs, Moderation, streamResponse } from '../../moderation/Moderation' import { formatResponse } from '../../outputparsers/OutputParserHelpers' class MultiPromptChain_Chains implements INode { label: string name: string version: number type: string icon: string category: string baseClasses: string[] description: string inputs: INodeParams[] badge: string constructor() { this.label = 'Multi Prompt Chain' this.name = 'multiPromptChain' this.version = 2.0 this.badge = 'DEPRECATING' this.type = 'MultiPromptChain' this.icon = 'prompt.svg' this.category = 'Chains' this.description = 'Chain automatically picks an appropriate prompt from multiple prompt templates' this.baseClasses = [this.type, ...getBaseClasses(MultiPromptChain)] this.inputs = [ { label: 'Language Model', name: 'model', type: 'BaseLanguageModel' }, { label: 'Prompt Retriever', name: 'promptRetriever', type: 'PromptRetriever', list: true }, { label: 'Input Moderation', description: 'Detect text that could generate harmful output and prevent it from being sent to the language model', name: 'inputModeration', type: 'Moderation', optional: true, list: true } ] } async init(nodeData: INodeData): Promise { const model = nodeData.inputs?.model as BaseLanguageModel const promptRetriever = nodeData.inputs?.promptRetriever as PromptRetriever[] const promptNames = [] const promptDescriptions = [] const promptTemplates = [] for (const prompt of promptRetriever) { promptNames.push(prompt.name) promptDescriptions.push(prompt.description) promptTemplates.push(prompt.systemMessage) } const chain = MultiPromptChain.fromLLMAndPrompts(model, { promptNames, promptDescriptions, promptTemplates, llmChainOpts: { verbose: process.env.DEBUG === 'true' ? true : false } }) return chain } async run(nodeData: INodeData, input: string, options: ICommonObject): Promise { const chain = nodeData.instance as MultiPromptChain const moderations = nodeData.inputs?.inputModeration as Moderation[] // this is true if the prediction is external and the client has requested streaming='true' const shouldStreamResponse = options.shouldStreamResponse const sseStreamer: IServerSideEventStreamer = options.sseStreamer as IServerSideEventStreamer const chatId = options.chatId if (moderations && moderations.length > 0) { try { // Use the output of the moderation chain as input for the Multi Prompt Chain input = await checkInputs(moderations, input) } catch (e) { await new Promise((resolve) => setTimeout(resolve, 500)) if (options.shouldStreamResponse) { streamResponse(options.sseStreamer, options.chatId, e.message) } return formatResponse(e.message) } } const obj = { input } const loggerHandler = new ConsoleCallbackHandler(options.logger, options?.orgId) const callbacks = await additionalCallbacks(nodeData, options) if (shouldStreamResponse) { const handler = new CustomChainHandler(sseStreamer, chatId, 2) const res = await chain.call(obj, [loggerHandler, handler, ...callbacks]) return res?.text } else { const res = await chain.call(obj, [loggerHandler, ...callbacks]) return res?.text } } } module.exports = { nodeClass: MultiPromptChain_Chains }