Add input moderation for all chains and agents

packages/components/nodes/agents/AirtableAgent/AirtableAgent.ts

@@ -6,6 +6,8 @@ import { ICommonObject, INode, INodeData, INodeParams, PromptTemplate } from '..
 import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
 import { ConsoleCallbackHandler, CustomChainHandler, additionalCallbacks } from '../../../src/handler'
 import { LoadPyodide, finalSystemPrompt, systemPrompt } from './core'
+import { checkInputs, Moderation } from '../../moderation/Moderation'
+import { formatResponse } from '../../outputparsers/OutputParserHelpers'
 
 class Airtable_Agents implements INode {
     label: string
@@ -22,7 +24,7 @@ class Airtable_Agents implements INode {
     constructor() {
         this.label = 'Airtable Agent'
         this.name = 'airtableAgent'
-        this.version = 1.0
+        this.version = 2.0
         this.type = 'AgentExecutor'
         this.category = 'Agents'
         this.icon = 'airtable.svg'
@@ -71,6 +73,14 @@ class Airtable_Agents implements INode {
                 default: 100,
                 additionalParams: true,
                 description: 'Number of results to return'
+            },
+            {
+                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
             }
         ]
     }
@@ -80,12 +90,24 @@ class Airtable_Agents implements INode {
         return undefined
     }
 
-    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
+    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | object> {
         const model = nodeData.inputs?.model as BaseLanguageModel
         const baseId = nodeData.inputs?.baseId as string
         const tableId = nodeData.inputs?.tableId as string
         const returnAll = nodeData.inputs?.returnAll as boolean
         const limit = nodeData.inputs?.limit as string
+        const moderations = nodeData.inputs?.inputModeration as Moderation[]
+
+        if (moderations && moderations.length > 0) {
+            try {
+                // Use the output of the moderation chain as input for the Vectara chain
+                input = await checkInputs(moderations, input)
+            } catch (e) {
+                await new Promise((resolve) => setTimeout(resolve, 500))
+                //streamResponse(options.socketIO && options.socketIOClientId, e.message, options.socketIO, options.socketIOClientId)
+                return formatResponse(e.message)
+            }
+        }
 
         const credentialData = await getCredentialData(nodeData.credential ?? '', options)
         const accessToken = getCredentialParam('accessToken', credentialData, nodeData)

packages/components/nodes/agents/AutoGPT/AutoGPT.ts

@@ -7,6 +7,8 @@ import { PromptTemplate } from '@langchain/core/prompts'
 import { AutoGPT } from 'langchain/experimental/autogpt'
 import { LLMChain } from 'langchain/chains'
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
+import { checkInputs, Moderation } from '../../moderation/Moderation'
+import { formatResponse } from '../../outputparsers/OutputParserHelpers'
 
 type ObjectTool = StructuredTool
 const FINISH_NAME = 'finish'
@@ -25,7 +27,7 @@ class AutoGPT_Agents implements INode {
     constructor() {
         this.label = 'AutoGPT'
         this.name = 'autoGPT'
-        this.version = 1.0
+        this.version = 2.0
         this.type = 'AutoGPT'
         this.category = 'Agents'
         this.icon = 'autogpt.svg'
@@ -68,6 +70,14 @@ class AutoGPT_Agents implements INode {
                 type: 'number',
                 default: 5,
                 optional: 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
             }
         ]
     }
@@ -92,9 +102,21 @@ class AutoGPT_Agents implements INode {
         return autogpt
     }
 
-    async run(nodeData: INodeData, input: string): Promise<string> {
+    async run(nodeData: INodeData, input: string): Promise<string | object> {
         const executor = nodeData.instance as AutoGPT
         const model = nodeData.inputs?.model as BaseChatModel
+        const moderations = nodeData.inputs?.inputModeration as Moderation[]
+
+        if (moderations && moderations.length > 0) {
+            try {
+                // Use the output of the moderation chain as input for the AutoGPT agent
+                input = await checkInputs(moderations, input)
+            } catch (e) {
+                await new Promise((resolve) => setTimeout(resolve, 500))
+                //streamResponse(options.socketIO && options.socketIOClientId, e.message, options.socketIO, options.socketIOClientId)
+                return formatResponse(e.message)
+            }
+        }
 
         try {
             let totalAssistantReply = ''

packages/components/nodes/agents/BabyAGI/BabyAGI.ts

@@ -2,6 +2,8 @@ import { BaseChatModel } from '@langchain/core/language_models/chat_models'
 import { VectorStore } from '@langchain/core/vectorstores'
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { BabyAGI } from './core'
+import { checkInputs, Moderation } from '../../moderation/Moderation'
+import { formatResponse } from '../../outputparsers/OutputParserHelpers'
 
 class BabyAGI_Agents implements INode {
     label: string
@@ -17,7 +19,7 @@ class BabyAGI_Agents implements INode {
     constructor() {
         this.label = 'BabyAGI'
         this.name = 'babyAGI'
-        this.version = 1.0
+        this.version = 2.0
         this.type = 'BabyAGI'
         this.category = 'Agents'
         this.icon = 'babyagi.svg'
@@ -39,6 +41,14 @@ class BabyAGI_Agents implements INode {
                 name: 'taskLoop',
                 type: 'number',
                 default: 3
+            },
+            {
+                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
             }
         ]
     }
@@ -53,8 +63,21 @@ class BabyAGI_Agents implements INode {
         return babyAgi
     }
 
-    async run(nodeData: INodeData, input: string): Promise<string> {
+    async run(nodeData: INodeData, input: string): Promise<string | object> {
         const executor = nodeData.instance as BabyAGI
+        const moderations = nodeData.inputs?.inputModeration as Moderation[]
+
+        if (moderations && moderations.length > 0) {
+            try {
+                // Use the output of the moderation chain as input for the BabyAGI agent
+                input = await checkInputs(moderations, input)
+            } catch (e) {
+                await new Promise((resolve) => setTimeout(resolve, 500))
+                //streamResponse(options.socketIO && options.socketIOClientId, e.message, options.socketIO, options.socketIOClientId)
+                return formatResponse(e.message)
+            }
+        }
+
         const objective = input
 
         const res = await executor.call({ objective })

packages/components/nodes/agents/CSVAgent/CSVAgent.ts

@@ -5,6 +5,8 @@ import { ConsoleCallbackHandler, CustomChainHandler, additionalCallbacks } from
 import { ICommonObject, INode, INodeData, INodeParams, PromptTemplate } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
 import { LoadPyodide, finalSystemPrompt, systemPrompt } from './core'
+import { checkInputs, Moderation } from '../../moderation/Moderation'
+import { formatResponse } from '../../outputparsers/OutputParserHelpers'
 
 class CSV_Agents implements INode {
     label: string
@@ -20,7 +22,7 @@ class CSV_Agents implements INode {
     constructor() {
         this.label = 'CSV Agent'
         this.name = 'csvAgent'
-        this.version = 1.0
+        this.version = 2.0
         this.type = 'AgentExecutor'
         this.category = 'Agents'
         this.icon = 'CSVagent.svg'
@@ -47,6 +49,14 @@ class CSV_Agents implements INode {
                 optional: true,
                 placeholder:
                     'I want you to act as a document that I am having a conversation with. Your name is "AI Assistant". You will provide me with answers from the given info. If the answer is not included, say exactly "Hmm, I am not sure." and stop after that. Refuse to answer any question not about the info. Never break character.'
+            },
+            {
+                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
             }
         ]
     }
@@ -56,10 +66,22 @@ class CSV_Agents implements INode {
         return undefined
     }
 
-    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
+    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | object> {
         const csvFileBase64 = nodeData.inputs?.csvFile as string
         const model = nodeData.inputs?.model as BaseLanguageModel
         const systemMessagePrompt = nodeData.inputs?.systemMessagePrompt as string
+        const moderations = nodeData.inputs?.inputModeration as Moderation[]
+
+        if (moderations && moderations.length > 0) {
+            try {
+                // Use the output of the moderation chain as input for the CSV agent
+                input = await checkInputs(moderations, input)
+            } catch (e) {
+                await new Promise((resolve) => setTimeout(resolve, 500))
+                //streamResponse(options.socketIO && options.socketIOClientId, e.message, options.socketIO, options.socketIOClientId)
+                return formatResponse(e.message)
+            }
+        }
 
         const loggerHandler = new ConsoleCallbackHandler(options.logger)
         const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId)

packages/components/nodes/agents/ConversationalAgent/ConversationalAgent.ts

@@ -13,6 +13,8 @@ import { FlowiseMemory, ICommonObject, IMessage, INode, INodeData, INodeParams }
 import { AgentExecutor } from '../../../src/agents'
 import { ChatOpenAI } from '../../chatmodels/ChatOpenAI/FlowiseChatOpenAI'
 import { addImagesToMessages } from '../../../src/multiModalUtils'
+import { checkInputs, Moderation } from '../../moderation/Moderation'
+import { formatResponse } from '../../outputparsers/OutputParserHelpers'
 
 const DEFAULT_PREFIX = `Assistant is a large language model trained by OpenAI.
 
@@ -46,7 +48,7 @@ class ConversationalAgent_Agents implements INode {
     constructor(fields?: { sessionId?: string }) {
         this.label = 'Conversational Agent'
         this.name = 'conversationalAgent'
-        this.version = 2.0
+        this.version = 3.0
         this.type = 'AgentExecutor'
         this.category = 'Agents'
         this.icon = 'agent.svg'
@@ -77,6 +79,14 @@ class ConversationalAgent_Agents implements INode {
                 default: DEFAULT_PREFIX,
                 optional: true,
                 additionalParams: 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
             }
         ]
         this.sessionId = fields?.sessionId
@@ -86,9 +96,20 @@ class ConversationalAgent_Agents implements INode {
         return prepareAgent(nodeData, options, { sessionId: this.sessionId, chatId: options.chatId, input }, options.chatHistory)
     }
 
-    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
+    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | object> {
         const memory = nodeData.inputs?.memory as FlowiseMemory
+        const moderations = nodeData.inputs?.inputModeration as Moderation[]
 
+        if (moderations && moderations.length > 0) {
+            try {
+                // Use the output of the moderation chain as input for the BabyAGI agent
+                input = await checkInputs(moderations, input)
+            } catch (e) {
+                await new Promise((resolve) => setTimeout(resolve, 500))
+                //streamResponse(options.socketIO && options.socketIOClientId, e.message, options.socketIO, options.socketIOClientId)
+                return formatResponse(e.message)
+            }
+        }
         const executor = await prepareAgent(
             nodeData,
             options,

packages/components/nodes/agents/ConversationalRetrievalAgent/ConversationalRetrievalAgent.ts

@@ -10,6 +10,8 @@ import { FlowiseMemory, ICommonObject, IMessage, INode, INodeData, INodeParams }
 import { getBaseClasses } from '../../../src/utils'
 import { ConsoleCallbackHandler, CustomChainHandler, additionalCallbacks } from '../../../src/handler'
 import { AgentExecutor, formatAgentSteps } from '../../../src/agents'
+import { checkInputs, Moderation } from '../../moderation/Moderation'
+import { formatResponse } from '../../outputparsers/OutputParserHelpers'
 
 const defaultMessage = `Do your best to answer the questions. Feel free to use any tools available to look up relevant information, only if necessary.`
 
@@ -28,7 +30,7 @@ class ConversationalRetrievalAgent_Agents implements INode {
     constructor(fields?: { sessionId?: string }) {
         this.label = 'Conversational Retrieval Agent'
         this.name = 'conversationalRetrievalAgent'
-        this.version = 3.0
+        this.version = 4.0
         this.type = 'AgentExecutor'
         this.category = 'Agents'
         this.icon = 'agent.svg'
@@ -59,6 +61,14 @@ class ConversationalRetrievalAgent_Agents implements INode {
                 rows: 4,
                 optional: true,
                 additionalParams: 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
             }
         ]
         this.sessionId = fields?.sessionId
@@ -68,8 +78,21 @@ class ConversationalRetrievalAgent_Agents implements INode {
         return prepareAgent(nodeData, { sessionId: this.sessionId, chatId: options.chatId, input }, options.chatHistory)
     }
 
-    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
+    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | object> {
         const memory = nodeData.inputs?.memory as FlowiseMemory
+        const moderations = nodeData.inputs?.inputModeration as Moderation[]
+
+        if (moderations && moderations.length > 0) {
+            try {
+                // Use the output of the moderation chain as input for the BabyAGI agent
+                input = await checkInputs(moderations, input)
+            } catch (e) {
+                await new Promise((resolve) => setTimeout(resolve, 500))
+                //streamResponse(options.socketIO && options.socketIOClientId, e.message, options.socketIO, options.socketIOClientId)
+                return formatResponse(e.message)
+            }
+        }
+
         const executor = prepareAgent(nodeData, { sessionId: this.sessionId, chatId: options.chatId, input }, options.chatHistory)
 
         const loggerHandler = new ConsoleCallbackHandler(options.logger)

packages/components/nodes/agents/MRKLAgentChat/MRKLAgentChat.ts

@@ -12,6 +12,8 @@ import { getBaseClasses } from '../../../src/utils'
 import { createReactAgent } from '../../../src/agents'
 import { ChatOpenAI } from '../../chatmodels/ChatOpenAI/FlowiseChatOpenAI'
 import { addImagesToMessages } from '../../../src/multiModalUtils'
+import { checkInputs, Moderation } from '../../moderation/Moderation'
+import { formatResponse } from '../../outputparsers/OutputParserHelpers'
 
 class MRKLAgentChat_Agents implements INode {
     label: string
@@ -28,7 +30,7 @@ class MRKLAgentChat_Agents implements INode {
     constructor(fields?: { sessionId?: string }) {
         this.label = 'ReAct Agent for Chat Models'
         this.name = 'mrklAgentChat'
-        this.version = 3.0
+        this.version = 4.0
         this.type = 'AgentExecutor'
         this.category = 'Agents'
         this.icon = 'agent.svg'
@@ -50,6 +52,14 @@ class MRKLAgentChat_Agents implements INode {
                 label: 'Memory',
                 name: 'memory',
                 type: 'BaseChatMemory'
+            },
+            {
+                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
             }
         ]
         this.sessionId = fields?.sessionId
@@ -59,10 +69,22 @@ class MRKLAgentChat_Agents implements INode {
         return null
     }
 
-    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
+    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | object> {
         const memory = nodeData.inputs?.memory as FlowiseMemory
         const model = nodeData.inputs?.model as BaseChatModel
         let tools = nodeData.inputs?.tools as Tool[]
+        const moderations = nodeData.inputs?.inputModeration as Moderation[]
+
+        if (moderations && moderations.length > 0) {
+            try {
+                // Use the output of the moderation chain as input for the ReAct Agent for Chat Models
+                input = await checkInputs(moderations, input)
+            } catch (e) {
+                await new Promise((resolve) => setTimeout(resolve, 500))
+                //streamResponse(options.socketIO && options.socketIOClientId, e.message, options.socketIO, options.socketIOClientId)
+                return formatResponse(e.message)
+            }
+        }
         tools = flatten(tools)
 
         const prompt = await pull<PromptTemplate>('hwchase17/react-chat')

packages/components/nodes/agents/MRKLAgentLLM/MRKLAgentLLM.ts

@@ -8,6 +8,8 @@ import { additionalCallbacks } from '../../../src/handler'
 import { getBaseClasses } from '../../../src/utils'
 import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { createReactAgent } from '../../../src/agents'
+import { checkInputs, Moderation } from '../../moderation/Moderation'
+import { formatResponse } from '../../outputparsers/OutputParserHelpers'
 
 class MRKLAgentLLM_Agents implements INode {
     label: string
@@ -23,7 +25,7 @@ class MRKLAgentLLM_Agents implements INode {
     constructor() {
         this.label = 'ReAct Agent for LLMs'
         this.name = 'mrklAgentLLM'
-        this.version = 1.0
+        this.version = 2.0
         this.type = 'AgentExecutor'
         this.category = 'Agents'
         this.icon = 'agent.svg'
@@ -40,6 +42,14 @@ class MRKLAgentLLM_Agents implements INode {
                 label: 'Language Model',
                 name: 'model',
                 type: 'BaseLanguageModel'
+            },
+            {
+                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
             }
         ]
     }
@@ -48,9 +58,22 @@ class MRKLAgentLLM_Agents implements INode {
         return null
     }
 
-    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
+    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | object> {
         const model = nodeData.inputs?.model as BaseLanguageModel
         let tools = nodeData.inputs?.tools as Tool[]
+        const moderations = nodeData.inputs?.inputModeration as Moderation[]
+
+        if (moderations && moderations.length > 0) {
+            try {
+                // Use the output of the moderation chain as input for the ReAct Agent for LLMs
+                input = await checkInputs(moderations, input)
+            } catch (e) {
+                await new Promise((resolve) => setTimeout(resolve, 500))
+                //streamResponse(options.socketIO && options.socketIOClientId, e.message, options.socketIO, options.socketIOClientId)
+                return formatResponse(e.message)
+            }
+        }
+
         tools = flatten(tools)
 
         const prompt = await pull<PromptTemplate>('hwchase17/react')

packages/components/nodes/agents/OpenAIFunctionAgent/OpenAIFunctionAgent.ts

@@ -10,6 +10,8 @@ import { getBaseClasses } from '../../../src/utils'
 import { FlowiseMemory, ICommonObject, IMessage, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { ConsoleCallbackHandler, CustomChainHandler, additionalCallbacks } from '../../../src/handler'
 import { AgentExecutor, formatAgentSteps } from '../../../src/agents'
+import { Moderation, checkInputs } from '../../moderation/Moderation'
+import { formatResponse } from '../../outputparsers/OutputParserHelpers'
 
 class OpenAIFunctionAgent_Agents implements INode {
     label: string
@@ -26,7 +28,7 @@ class OpenAIFunctionAgent_Agents implements INode {
     constructor(fields?: { sessionId?: string }) {
         this.label = 'OpenAI Function Agent'
         this.name = 'openAIFunctionAgent'
-        this.version = 3.0
+        this.version = 4.0
         this.type = 'AgentExecutor'
         this.category = 'Agents'
         this.icon = 'function.svg'
@@ -56,6 +58,14 @@ class OpenAIFunctionAgent_Agents implements INode {
                 rows: 4,
                 optional: true,
                 additionalParams: 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
             }
         ]
         this.sessionId = fields?.sessionId
@@ -67,6 +77,19 @@ class OpenAIFunctionAgent_Agents implements INode {
 
     async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | ICommonObject> {
         const memory = nodeData.inputs?.memory as FlowiseMemory
+        const moderations = nodeData.inputs?.inputModeration as Moderation[]
+
+        if (moderations && moderations.length > 0) {
+            try {
+                // Use the output of the moderation chain as input for the OpenAI Function Agent
+                input = await checkInputs(moderations, input)
+            } catch (e) {
+                await new Promise((resolve) => setTimeout(resolve, 500))
+                //streamResponse(options.socketIO && options.socketIOClientId, e.message, options.socketIO, options.socketIOClientId)
+                return formatResponse(e.message)
+            }
+        }
+
         const executor = prepareAgent(nodeData, { sessionId: this.sessionId, chatId: options.chatId, input }, options.chatHistory)
 
         const loggerHandler = new ConsoleCallbackHandler(options.logger)

packages/components/nodes/agents/XMLAgent/XMLAgent.ts

@@ -11,7 +11,8 @@ import { getBaseClasses } from '../../../src/utils'
 import { FlowiseMemory, ICommonObject, IMessage, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { ConsoleCallbackHandler, CustomChainHandler, additionalCallbacks } from '../../../src/handler'
 import { AgentExecutor } from '../../../src/agents'
-//import { AgentExecutor } from "langchain/agents";
+import { Moderation, checkInputs } from '../../moderation/Moderation'
+import { formatResponse } from '../../outputparsers/OutputParserHelpers'
 
 const defaultSystemMessage = `You are a helpful assistant. Help the user answer any questions.
 
@@ -52,7 +53,7 @@ class XMLAgent_Agents implements INode {
     constructor(fields?: { sessionId?: string }) {
         this.label = 'XML Agent'
         this.name = 'xmlAgent'
-        this.version = 1.0
+        this.version = 2.0
         this.type = 'XMLAgent'
         this.category = 'Agents'
         this.icon = 'xmlagent.svg'
@@ -83,6 +84,14 @@ class XMLAgent_Agents implements INode {
                 rows: 4,
                 default: defaultSystemMessage,
                 additionalParams: 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
             }
         ]
         this.sessionId = fields?.sessionId
@@ -94,6 +103,18 @@ class XMLAgent_Agents implements INode {
 
     async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | ICommonObject> {
         const memory = nodeData.inputs?.memory as FlowiseMemory
+        const moderations = nodeData.inputs?.inputModeration as Moderation[]
+
+        if (moderations && moderations.length > 0) {
+            try {
+                // Use the output of the moderation chain as input for the OpenAI Function Agent
+                input = await checkInputs(moderations, input)
+            } catch (e) {
+                await new Promise((resolve) => setTimeout(resolve, 500))
+                //streamResponse(options.socketIO && options.socketIOClientId, e.message, options.socketIO, options.socketIOClientId)
+                return formatResponse(e.message)
+            }
+        }
         const executor = await prepareAgent(nodeData, { sessionId: this.sessionId, chatId: options.chatId, input }, options.chatHistory)
 
         const loggerHandler = new ConsoleCallbackHandler(options.logger)