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)

packages/components/nodes/chains/ApiChain/OpenAPIChain.ts

@@ -3,6 +3,8 @@ import { APIChain, createOpenAPIChain } from 'langchain/chains'
 import { ICommonObject, INode, INodeData, INodeParams } 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 OpenApiChain_Chains implements INode {
     label: string
@@ -18,7 +20,7 @@ class OpenApiChain_Chains implements INode {
     constructor() {
         this.label = 'OpenAPI Chain'
         this.name = 'openApiChain'
-        this.version = 1.0
+        this.version = 2.0
         this.type = 'OpenAPIChain'
         this.icon = 'openapi.svg'
         this.category = 'Chains'
@@ -50,6 +52,14 @@ class OpenApiChain_Chains implements INode {
                 type: 'json',
                 additionalParams: true,
                 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
             }
         ]
     }
@@ -58,11 +68,21 @@ class OpenApiChain_Chains implements INode {
         return await initChain(nodeData)
     }
 
-    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
+    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | object> {
         const chain = await initChain(nodeData)
         const loggerHandler = new ConsoleCallbackHandler(options.logger)
         const callbacks = await additionalCallbacks(nodeData, options)
-
+        const moderations = nodeData.inputs?.inputModeration as Moderation[]
+        if (moderations && moderations.length > 0) {
+            try {
+                // Use the output of the moderation chain as input for the OpenAPI 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)
+            }
+        }
         if (options.socketIO && options.socketIOClientId) {
             const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId)
             const res = await chain.run(input, [loggerHandler, handler, ...callbacks])

packages/components/nodes/chains/ConversationalRetrievalQAChain/ConversationalRetrievalQAChain.ts

@@ -5,6 +5,8 @@ import { PromptTemplate, ChatPromptTemplate, MessagesPlaceholder } from '@langch
 import { Runnable, RunnableSequence, RunnableMap, RunnableBranch, RunnableLambda } from '@langchain/core/runnables'
 import { BaseMessage, HumanMessage, AIMessage } from '@langchain/core/messages'
 import { ConsoleCallbackHandler as LCConsoleCallbackHandler } from '@langchain/core/tracers/console'
+import { checkInputs, Moderation, streamResponse } from '../../moderation/Moderation'
+import { formatResponse } from '../../outputparsers/OutputParserHelpers'
 import { StringOutputParser } from '@langchain/core/output_parsers'
 import type { Document } from '@langchain/core/documents'
 import { BufferMemoryInput } from 'langchain/memory'
@@ -36,7 +38,7 @@ class ConversationalRetrievalQAChain_Chains implements INode {
     constructor(fields?: { sessionId?: string }) {
         this.label = 'Conversational Retrieval QA Chain'
         this.name = 'conversationalRetrievalQAChain'
-        this.version = 2.0
+        this.version = 3.0
         this.type = 'ConversationalRetrievalQAChain'
         this.icon = 'qa.svg'
         this.category = 'Chains'
@@ -87,6 +89,14 @@ class ConversationalRetrievalQAChain_Chains implements INode {
                 additionalParams: true,
                 optional: true,
                 default: RESPONSE_TEMPLATE
+            },
+            {
+                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
             }
             /** Deprecated
             {
@@ -163,6 +173,7 @@ class ConversationalRetrievalQAChain_Chains implements INode {
         }
 
         let memory: FlowiseMemory | undefined = externalMemory
+        const moderations = nodeData.inputs?.inputModeration as Moderation[]
         if (!memory) {
             memory = new BufferMemory({
                 returnMessages: true,
@@ -171,6 +182,16 @@ class ConversationalRetrievalQAChain_Chains implements INode {
             })
         }
 
+        if (moderations && moderations.length > 0) {
+            try {
+                // Use the output of the moderation chain as input for the Conversational Retrieval QA 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 answerChain = createChain(model, vectorStoreRetriever, rephrasePrompt, customResponsePrompt)
 
         const history = ((await memory.getChatMessages(this.sessionId, false, options.chatHistory)) as IMessage[]) ?? []

packages/components/nodes/chains/MultiPromptChain/MultiPromptChain.ts

@@ -3,6 +3,8 @@ import { MultiPromptChain } from 'langchain/chains'
 import { ICommonObject, INode, INodeData, INodeParams, 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
@@ -18,7 +20,7 @@ class MultiPromptChain_Chains implements INode {
     constructor() {
         this.label = 'Multi Prompt Chain'
         this.name = 'multiPromptChain'
-        this.version = 1.0
+        this.version = 2.0
         this.type = 'MultiPromptChain'
         this.icon = 'prompt.svg'
         this.category = 'Chains'
@@ -35,6 +37,14 @@ class MultiPromptChain_Chains implements INode {
                 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
             }
         ]
     }
@@ -62,8 +72,19 @@ class MultiPromptChain_Chains implements INode {
         return chain
     }
 
-    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
+    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | object> {
         const chain = nodeData.instance as MultiPromptChain
+        const moderations = nodeData.inputs?.inputModeration as Moderation[]
+        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))
+                streamResponse(options.socketIO && options.socketIOClientId, e.message, options.socketIO, options.socketIOClientId)
+                return formatResponse(e.message)
+            }
+        }
         const obj = { input }
 
         const loggerHandler = new ConsoleCallbackHandler(options.logger)

packages/components/nodes/chains/MultiRetrievalQAChain/MultiRetrievalQAChain.ts

@@ -3,6 +3,8 @@ import { MultiRetrievalQAChain } from 'langchain/chains'
 import { ICommonObject, INode, INodeData, INodeParams, VectorStoreRetriever } 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 MultiRetrievalQAChain_Chains implements INode {
     label: string
@@ -18,7 +20,7 @@ class MultiRetrievalQAChain_Chains implements INode {
     constructor() {
         this.label = 'Multi Retrieval QA Chain'
         this.name = 'multiRetrievalQAChain'
-        this.version = 1.0
+        this.version = 2.0
         this.type = 'MultiRetrievalQAChain'
         this.icon = 'qa.svg'
         this.category = 'Chains'
@@ -41,6 +43,14 @@ class MultiRetrievalQAChain_Chains implements INode {
                 name: 'returnSourceDocuments',
                 type: 'boolean',
                 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
             }
         ]
     }
@@ -72,7 +82,17 @@ class MultiRetrievalQAChain_Chains implements INode {
     async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | ICommonObject> {
         const chain = nodeData.instance as MultiRetrievalQAChain
         const returnSourceDocuments = nodeData.inputs?.returnSourceDocuments as boolean
-
+        const moderations = nodeData.inputs?.inputModeration as Moderation[]
+        if (moderations && moderations.length > 0) {
+            try {
+                // Use the output of the moderation chain as input for the Multi Retrieval QA 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 obj = { input }
         const loggerHandler = new ConsoleCallbackHandler(options.logger)
         const callbacks = await additionalCallbacks(nodeData, options)

packages/components/nodes/chains/RetrievalQAChain/RetrievalQAChain.ts

@@ -4,6 +4,8 @@ import { RetrievalQAChain } from 'langchain/chains'
 import { ConsoleCallbackHandler, CustomChainHandler, additionalCallbacks } from '../../../src/handler'
 import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
+import { checkInputs, Moderation, streamResponse } from '../../moderation/Moderation'
+import { formatResponse } from '../../outputparsers/OutputParserHelpers'
 
 class RetrievalQAChain_Chains implements INode {
     label: string
@@ -19,7 +21,7 @@ class RetrievalQAChain_Chains implements INode {
     constructor() {
         this.label = 'Retrieval QA Chain'
         this.name = 'retrievalQAChain'
-        this.version = 1.0
+        this.version = 2.0
         this.type = 'RetrievalQAChain'
         this.icon = 'qa.svg'
         this.category = 'Chains'
@@ -35,6 +37,14 @@ class RetrievalQAChain_Chains implements INode {
                 label: 'Vector Store Retriever',
                 name: 'vectorStoreRetriever',
                 type: 'BaseRetriever'
+            },
+            {
+                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
             }
         ]
     }
@@ -47,8 +57,19 @@ class RetrievalQAChain_Chains implements INode {
         return chain
     }
 
-    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
+    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | object> {
         const chain = nodeData.instance as RetrievalQAChain
+        const moderations = nodeData.inputs?.inputModeration as Moderation[]
+        if (moderations && moderations.length > 0) {
+            try {
+                // Use the output of the moderation chain as input for the Retrieval QA 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 obj = {
             query: input
         }

packages/components/nodes/chains/SqlDatabaseChain/SqlDatabaseChain.ts

@@ -7,6 +7,8 @@ import { SqlDatabase } from 'langchain/sql_db'
 import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { ConsoleCallbackHandler, CustomChainHandler, additionalCallbacks } from '../../../src/handler'
 import { getBaseClasses, getInputVariables } from '../../../src/utils'
+import { checkInputs, Moderation, streamResponse } from '../../moderation/Moderation'
+import { formatResponse } from '../../outputparsers/OutputParserHelpers'
 
 type DatabaseType = 'sqlite' | 'postgres' | 'mssql' | 'mysql'
 
@@ -24,7 +26,7 @@ class SqlDatabaseChain_Chains implements INode {
     constructor() {
         this.label = 'Sql Database Chain'
         this.name = 'sqlDatabaseChain'
-        this.version = 4.0
+        this.version = 5.0
         this.type = 'SqlDatabaseChain'
         this.icon = 'sqlchain.svg'
         this.category = 'Chains'
@@ -115,6 +117,14 @@ class SqlDatabaseChain_Chains implements INode {
                 placeholder: DEFAULT_SQL_DATABASE_PROMPT.template + DEFAULT_SQL_DATABASE_PROMPT.templateFormat,
                 additionalParams: true,
                 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
             }
         ]
     }
@@ -144,7 +154,7 @@ class SqlDatabaseChain_Chains implements INode {
         return chain
     }
 
-    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
+    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | object> {
         const databaseType = nodeData.inputs?.database as DatabaseType
         const model = nodeData.inputs?.model as BaseLanguageModel
         const url = nodeData.inputs?.url as string
@@ -155,6 +165,17 @@ class SqlDatabaseChain_Chains implements INode {
         const sampleRowsInTableInfo = nodeData.inputs?.sampleRowsInTableInfo as number
         const topK = nodeData.inputs?.topK as number
         const customPrompt = nodeData.inputs?.customPrompt 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 Sql Database 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 chain = await getSQLDBChain(
             databaseType,

packages/components/nodes/chains/VectaraChain/VectaraChain.ts

@@ -4,6 +4,8 @@ import { VectaraStore } from '@langchain/community/vectorstores/vectara'
 import { VectorDBQAChain } from 'langchain/chains'
 import { INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
+import { checkInputs, Moderation } from '../../moderation/Moderation'
+import { formatResponse } from '../../outputparsers/OutputParserHelpers'
 
 // functionality based on https://github.com/vectara/vectara-answer
 const reorderCitations = (unorderedSummary: string) => {
@@ -48,7 +50,7 @@ class VectaraChain_Chains implements INode {
     constructor() {
         this.label = 'Vectara QA Chain'
         this.name = 'vectaraQAChain'
-        this.version = 1.0
+        this.version = 2.0
         this.type = 'VectaraQAChain'
         this.icon = 'vectara.png'
         this.category = 'Chains'
@@ -219,6 +221,14 @@ class VectaraChain_Chains implements INode {
                 description: 'Maximum results used to build the summarized response',
                 type: 'number',
                 default: 7
+            },
+            {
+                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
             }
         ]
     }
@@ -227,7 +237,7 @@ class VectaraChain_Chains implements INode {
         return null
     }
 
-    async run(nodeData: INodeData, input: string): Promise<object> {
+    async run(nodeData: INodeData, input: string): Promise<string | object> {
         const vectorStore = nodeData.inputs?.vectaraStore as VectaraStore
         const responseLang = (nodeData.inputs?.responseLang as string) ?? 'eng'
         const summarizerPromptName = nodeData.inputs?.summarizerPromptName as string
@@ -252,6 +262,18 @@ class VectaraChain_Chains implements INode {
         const mmrRerankerId = 272725718
         const mmrEnabled = vectaraFilter?.mmrConfig?.enabled
 
+        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 data = {
             query: [
                 {

packages/components/nodes/chains/VectorDBQAChain/VectorDBQAChain.ts

@@ -4,6 +4,8 @@ import { VectorDBQAChain } from 'langchain/chains'
 import { ConsoleCallbackHandler, CustomChainHandler, additionalCallbacks } from '../../../src/handler'
 import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
+import { checkInputs, Moderation } from '../../moderation/Moderation'
+import { formatResponse } from '../../outputparsers/OutputParserHelpers'
 
 class VectorDBQAChain_Chains implements INode {
     label: string
@@ -19,7 +21,7 @@ class VectorDBQAChain_Chains implements INode {
     constructor() {
         this.label = 'VectorDB QA Chain'
         this.name = 'vectorDBQAChain'
-        this.version = 1.0
+        this.version = 2.0
         this.type = 'VectorDBQAChain'
         this.icon = 'vectordb.svg'
         this.category = 'Chains'
@@ -35,6 +37,14 @@ class VectorDBQAChain_Chains implements INode {
                 label: 'Vector Store',
                 name: 'vectorStore',
                 type: 'VectorStore'
+            },
+            {
+                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
             }
         ]
     }
@@ -50,8 +60,20 @@ class VectorDBQAChain_Chains implements INode {
         return chain
     }
 
-    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
+    async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string | object> {
         const chain = nodeData.instance as VectorDBQAChain
+        const moderations = nodeData.inputs?.inputModeration as Moderation[]
+
+        if (moderations && moderations.length > 0) {
+            try {
+                // Use the output of the moderation chain as input for the VectorDB QA 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 obj = {
             query: input
         }

packages/server/marketplaces/chatflows/API Agent OpenAI.json

@@ -15,7 +15,7 @@
             "data": {
                 "id": "openApiChain_1",
                 "label": "OpenAPI Chain",
-                "version": 1,
+                "version": 2,
                 "name": "openApiChain",
                 "type": "OpenAPIChain",
                 "baseClasses": ["OpenAPIChain", "BaseChain"],
@@ -53,9 +53,19 @@
                         "name": "model",
                         "type": "ChatOpenAI",
                         "id": "openApiChain_1-input-model-ChatOpenAI"
+                    },
+                    {
+                        "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,
+                        "id": "openApiChain_1-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "model": "{{chatOpenAI_1.data.instance}}",
                     "yamlLink": "https://gist.githubusercontent.com/roaldnefs/053e505b2b7a807290908fe9aa3e1f00/raw/0a212622ebfef501163f91e23803552411ed00e4/openapi.yaml",
                     "headers": ""
@@ -399,7 +409,7 @@
                 "id": "openAIFunctionAgent_0",
                 "label": "OpenAI Function Agent",
                 "name": "openAIFunctionAgent",
-                "version": 3,
+                "version": 4,
                 "type": "AgentExecutor",
                 "baseClasses": ["AgentExecutor", "BaseChain"],
                 "category": "Agents",
@@ -434,9 +444,19 @@
                         "name": "model",
                         "type": "BaseChatModel",
                         "id": "openAIFunctionAgent_0-input-model-BaseChatModel"
+                    },
+                    {
+                        "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,
+                        "id": "openAIFunctionAgent_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "tools": ["{{chainTool_0.data.instance}}"],
                     "memory": "{{bufferMemory_0.data.instance}}",
                     "model": "{{chatOpenAI_2.data.instance}}",

packages/server/marketplaces/chatflows/API Agent.json

@@ -1100,7 +1100,7 @@
             "data": {
                 "id": "conversationalAgent_0",
                 "label": "Conversational Agent",
-                "version": 2,
+                "version": 3,
                 "name": "conversationalAgent",
                 "type": "AgentExecutor",
                 "baseClasses": ["AgentExecutor", "BaseChain", "Runnable"],
@@ -1137,9 +1137,19 @@
                         "name": "memory",
                         "type": "BaseChatMemory",
                         "id": "conversationalAgent_0-input-memory-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,
+                        "id": "conversationalAgent_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "tools": ["{{chainTool_0.data.instance}}", "{{chainTool_1.data.instance}}"],
                     "model": "{{chatOpenAI_3.data.instance}}",
                     "memory": "{{bufferMemory_0.data.instance}}",

packages/server/marketplaces/chatflows/AutoGPT.json

@@ -15,7 +15,7 @@
             "data": {
                 "id": "autoGPT_0",
                 "label": "AutoGPT",
-                "version": 1,
+                "version": 2,
                 "name": "autoGPT",
                 "type": "AutoGPT",
                 "baseClasses": ["AutoGPT"],
@@ -66,9 +66,19 @@
                         "name": "vectorStoreRetriever",
                         "type": "BaseRetriever",
                         "id": "autoGPT_0-input-vectorStoreRetriever-BaseRetriever"
+                    },
+                    {
+                        "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,
+                        "id": "autoGPT_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "tools": ["{{readFile_0.data.instance}}", "{{writeFile_1.data.instance}}", "{{serpAPI_0.data.instance}}"],
                     "model": "{{chatOpenAI_0.data.instance}}",
                     "vectorStoreRetriever": "{{pinecone_0.data.instance}}",

packages/server/marketplaces/chatflows/BabyAGI.json

@@ -15,7 +15,7 @@
             "data": {
                 "id": "babyAGI_1",
                 "label": "BabyAGI",
-                "version": 1,
+                "version": 2,
                 "name": "babyAGI",
                 "type": "BabyAGI",
                 "baseClasses": ["BabyAGI"],
@@ -42,9 +42,19 @@
                         "name": "vectorStore",
                         "type": "VectorStore",
                         "id": "babyAGI_1-input-vectorStore-VectorStore"
+                    },
+                    {
+                        "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,
+                        "id": "babyAGI_1-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "model": "{{chatOpenAI_0.data.instance}}",
                     "vectorStore": "{{pinecone_0.data.instance}}",
                     "taskLoop": 3

packages/server/marketplaces/chatflows/CSV Agent.json

@@ -16,7 +16,7 @@
                 "id": "csvAgent_0",
                 "label": "CSV Agent",
                 "name": "csvAgent",
-                "version": 1,
+                "version": 2,
                 "type": "AgentExecutor",
                 "baseClasses": ["AgentExecutor", "BaseChain"],
                 "category": "Agents",
@@ -36,9 +36,19 @@
                         "name": "model",
                         "type": "BaseLanguageModel",
                         "id": "csvAgent_0-input-model-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,
+                        "id": "csvAgent_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "model": "{{chatOpenAI_0.data.instance}}"
                 },
                 "outputAnchors": [

packages/server/marketplaces/chatflows/Chat with a Podcast.json

@@ -15,7 +15,7 @@
             "data": {
                 "id": "conversationalRetrievalQAChain_0",
                 "label": "Conversational Retrieval QA Chain",
-                "version": 2,
+                "version": 3,
                 "name": "conversationalRetrievalQAChain",
                 "type": "ConversationalRetrievalQAChain",
                 "baseClasses": ["ConversationalRetrievalQAChain", "BaseChain", "Runnable"],
@@ -74,9 +74,19 @@
                         "optional": true,
                         "description": "If left empty, a default BufferMemory will be used",
                         "id": "conversationalRetrievalQAChain_0-input-memory-BaseMemory"
+                    },
+                    {
+                        "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,
+                        "id": "conversationalRetrievalQAChain_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "model": "{{chatOpenAI_0.data.instance}}",
                     "vectorStoreRetriever": "{{memoryVectorStore_0.data.instance}}",
                     "memory": "",

packages/server/marketplaces/chatflows/ChatGPTPlugin.json

@@ -451,7 +451,7 @@
                 "id": "mrklAgentChat_0",
                 "label": "MRKL Agent for Chat Models",
                 "name": "mrklAgentChat",
-                "version": 1,
+                "version": 2,
                 "type": "AgentExecutor",
                 "baseClasses": ["AgentExecutor", "BaseChain"],
                 "category": "Agents",
@@ -470,9 +470,19 @@
                         "name": "model",
                         "type": "BaseLanguageModel",
                         "id": "mrklAgentChat_0-input-model-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,
+                        "id": "mrklAgentChat_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "tools": ["{{requestsGet_0.data.instance}}", "{{requestsPost_0.data.instance}}", "{{aiPlugin_0.data.instance}}"],
                     "model": "{{chatOpenAI_0.data.instance}}"
                 },

packages/server/marketplaces/chatflows/Conversational Agent.json

@@ -392,7 +392,7 @@
             "data": {
                 "id": "conversationalAgent_0",
                 "label": "Conversational Agent",
-                "version": 2,
+                "version": 3,
                 "name": "conversationalAgent",
                 "type": "AgentExecutor",
                 "baseClasses": ["AgentExecutor", "BaseChain", "Runnable"],
@@ -429,9 +429,19 @@
                         "name": "memory",
                         "type": "BaseChatMemory",
                         "id": "conversationalAgent_0-input-memory-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,
+                        "id": "conversationalAgent_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "tools": ["{{calculator_1.data.instance}}", "{{serpAPI_0.data.instance}}"],
                     "model": "{{chatOpenAI_0.data.instance}}",
                     "memory": "{{bufferMemory_1.data.instance}}",

packages/server/marketplaces/chatflows/Conversational Retrieval Agent.json

@@ -123,7 +123,7 @@
             "data": {
                 "id": "conversationalRetrievalAgent_0",
                 "label": "Conversational Retrieval Agent",
-                "version": 3,
+                "version": 4,
                 "name": "conversationalRetrievalAgent",
                 "type": "AgentExecutor",
                 "baseClasses": ["AgentExecutor", "BaseChain", "Runnable"],
@@ -159,9 +159,19 @@
                         "name": "model",
                         "type": "BaseChatModel",
                         "id": "conversationalRetrievalAgent_0-input-model-BaseChatModel"
+                    },
+                    {
+                        "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,
+                        "id": "conversationalRetrievalAgent_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "tools": ["{{retrieverTool_0.data.instance}}"],
                     "memory": "{{bufferMemory_0.data.instance}}",
                     "model": "{{chatOpenAI_0.data.instance}}",

packages/server/marketplaces/chatflows/Conversational Retrieval QA Chain.json

@@ -274,7 +274,7 @@
             "data": {
                 "id": "conversationalRetrievalQAChain_0",
                 "label": "Conversational Retrieval QA Chain",
-                "version": 2,
+                "version": 3,
                 "name": "conversationalRetrievalQAChain",
                 "type": "ConversationalRetrievalQAChain",
                 "baseClasses": ["ConversationalRetrievalQAChain", "BaseChain", "Runnable"],
@@ -333,9 +333,19 @@
                         "optional": true,
                         "description": "If left empty, a default BufferMemory will be used",
                         "id": "conversationalRetrievalQAChain_0-input-memory-BaseMemory"
+                    },
+                    {
+                        "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,
+                        "id": "conversationalRetrievalQAChain_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "model": "{{chatOpenAI_0.data.instance}}",
                     "vectorStoreRetriever": "{{pinecone_0.data.instance}}",
                     "memory": "",

packages/server/marketplaces/chatflows/Flowise Docs QnA.json

@@ -158,7 +158,7 @@
                 "id": "conversationalRetrievalQAChain_0",
                 "label": "Conversational Retrieval QA Chain",
                 "name": "conversationalRetrievalQAChain",
-                "version": 2,
+                "version": 3,
                 "type": "ConversationalRetrievalQAChain",
                 "baseClasses": ["ConversationalRetrievalQAChain", "BaseChain", "Runnable"],
                 "category": "Chains",
@@ -216,9 +216,19 @@
                         "optional": true,
                         "description": "If left empty, a default BufferMemory will be used",
                         "id": "conversationalRetrievalQAChain_0-input-memory-BaseMemory"
+                    },
+                    {
+                        "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,
+                        "id": "conversationalRetrievalQAChain_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "model": "{{chatOpenAI_0.data.instance}}",
                     "vectorStoreRetriever": "{{memoryVectorStore_0.data.instance}}",
                     "memory": "",

packages/server/marketplaces/chatflows/Local QnA.json

@@ -85,7 +85,7 @@
             "data": {
                 "id": "conversationalRetrievalQAChain_0",
                 "label": "Conversational Retrieval QA Chain",
-                "version": 2,
+                "version": 3,
                 "name": "conversationalRetrievalQAChain",
                 "type": "ConversationalRetrievalQAChain",
                 "baseClasses": ["ConversationalRetrievalQAChain", "BaseChain", "Runnable"],
@@ -144,9 +144,19 @@
                         "optional": true,
                         "description": "If left empty, a default BufferMemory will be used",
                         "id": "conversationalRetrievalQAChain_0-input-memory-BaseMemory"
+                    },
+                    {
+                        "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,
+                        "id": "conversationalRetrievalQAChain_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "model": "{{chatOllama_0.data.instance}}",
                     "vectorStoreRetriever": "{{faiss_0.data.instance}}",
                     "memory": "",

packages/server/marketplaces/chatflows/Long Term Memory.json

@@ -15,7 +15,7 @@
             "data": {
                 "id": "conversationalRetrievalQAChain_0",
                 "label": "Conversational Retrieval QA Chain",
-                "version": 2,
+                "version": 3,
                 "name": "conversationalRetrievalQAChain",
                 "type": "ConversationalRetrievalQAChain",
                 "baseClasses": ["ConversationalRetrievalQAChain", "BaseChain", "Runnable"],
@@ -74,9 +74,19 @@
                         "optional": true,
                         "description": "If left empty, a default BufferMemory will be used",
                         "id": "conversationalRetrievalQAChain_0-input-memory-BaseMemory"
+                    },
+                    {
+                        "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,
+                        "id": "conversationalRetrievalQAChain_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "model": "{{chatOpenAI_0.data.instance}}",
                     "vectorStoreRetriever": "{{qdrant_0.data.instance}}",
                     "memory": "{{ZepMemory_0.data.instance}}",

packages/server/marketplaces/chatflows/Metadata Filter.json

@@ -251,7 +251,7 @@
             "data": {
                 "id": "conversationalRetrievalQAChain_0",
                 "label": "Conversational Retrieval QA Chain",
-                "version": 2,
+                "version": 3,
                 "name": "conversationalRetrievalQAChain",
                 "type": "ConversationalRetrievalQAChain",
                 "baseClasses": ["ConversationalRetrievalQAChain", "BaseChain", "Runnable"],
@@ -310,9 +310,19 @@
                         "optional": true,
                         "description": "If left empty, a default BufferMemory will be used",
                         "id": "conversationalRetrievalQAChain_0-input-memory-BaseMemory"
+                    },
+                    {
+                        "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,
+                        "id": "conversationalRetrievalQAChain_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "model": "{{chatOpenAI_0.data.instance}}",
                     "vectorStoreRetriever": "{{pinecone_0.data.instance}}",
                     "rephrasePrompt": "Given the following conversation and a follow up question, rephrase the follow up question to be a standalone question.\n\nChat History:\n{chat_history}\nFollow Up Input: {question}\nStandalone Question:",

packages/server/marketplaces/chatflows/Multi Prompt Chain.json

@@ -84,7 +84,7 @@
                 "id": "multiPromptChain_0",
                 "label": "Multi Prompt Chain",
                 "name": "multiPromptChain",
-                "version": 1,
+                "version": 2,
                 "type": "MultiPromptChain",
                 "baseClasses": ["MultiPromptChain", "MultiRouteChain", "BaseChain", "BaseLangChain"],
                 "category": "Chains",
@@ -103,9 +103,19 @@
                         "type": "PromptRetriever",
                         "list": true,
                         "id": "multiPromptChain_0-input-promptRetriever-PromptRetriever"
+                    },
+                    {
+                        "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,
+                        "id": "multiPromptChain_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "model": "{{chatOpenAI_0.data.instance}}",
                     "promptRetriever": [
                         "{{promptRetriever_0.data.instance}}",

packages/server/marketplaces/chatflows/Multi Retrieval QA Chain.json

@@ -82,7 +82,7 @@
             "data": {
                 "id": "multiRetrievalQAChain_0",
                 "label": "Multi Retrieval QA Chain",
-                "version": 1,
+                "version": 2,
                 "name": "multiRetrievalQAChain",
                 "type": "MultiRetrievalQAChain",
                 "baseClasses": ["MultiRetrievalQAChain", "MultiRouteChain", "BaseChain", "BaseLangChain"],
@@ -109,9 +109,19 @@
                         "type": "VectorStoreRetriever",
                         "list": true,
                         "id": "multiRetrievalQAChain_0-input-vectorStoreRetriever-VectorStoreRetriever"
+                    },
+                    {
+                        "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,
+                        "id": "multiRetrievalQAChain_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "model": "{{chatOpenAI_0.data.instance}}",
                     "vectorStoreRetriever": [
                         "{{vectorStoreRetriever_0.data.instance}}",

packages/server/marketplaces/chatflows/Multiple VectorDB.json

@@ -163,7 +163,7 @@
             "data": {
                 "id": "retrievalQAChain_0",
                 "label": "Retrieval QA Chain",
-                "version": 1,
+                "version": 2,
                 "name": "retrievalQAChain",
                 "type": "RetrievalQAChain",
                 "baseClasses": ["RetrievalQAChain", "BaseChain", "BaseLangChain"],
@@ -182,9 +182,19 @@
                         "name": "vectorStoreRetriever",
                         "type": "BaseRetriever",
                         "id": "retrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever"
+                    },
+                    {
+                        "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,
+                        "id": "retrievalQAChain_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "model": "{{chatOpenAI_0.data.instance}}",
                     "vectorStoreRetriever": "{{redis_0.data.instance}}"
                 },
@@ -218,7 +228,7 @@
             "data": {
                 "id": "retrievalQAChain_1",
                 "label": "Retrieval QA Chain",
-                "version": 1,
+                "version": 2,
                 "name": "retrievalQAChain",
                 "type": "RetrievalQAChain",
                 "baseClasses": ["RetrievalQAChain", "BaseChain", "BaseLangChain"],
@@ -237,9 +247,19 @@
                         "name": "vectorStoreRetriever",
                         "type": "BaseRetriever",
                         "id": "retrievalQAChain_1-input-vectorStoreRetriever-BaseRetriever"
+                    },
+                    {
+                        "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,
+                        "id": "retrievalQAChain_1-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "model": "{{chatOpenAI_1.data.instance}}",
                     "vectorStoreRetriever": "{{faiss_0.data.instance}}"
                 },
@@ -1741,7 +1761,7 @@
             "data": {
                 "id": "conversationalAgent_0",
                 "label": "Conversational Agent",
-                "version": 2,
+                "version": 3,
                 "name": "conversationalAgent",
                 "type": "AgentExecutor",
                 "baseClasses": ["AgentExecutor", "BaseChain", "Runnable"],
@@ -1778,9 +1798,19 @@
                         "name": "memory",
                         "type": "BaseChatMemory",
                         "id": "conversationalAgent_0-input-memory-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,
+                        "id": "conversationalAgent_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "tools": ["{{chainTool_2.data.instance}}", "{{chainTool_3.data.instance}}"],
                     "model": "{{chatOpenAI_2.data.instance}}",
                     "memory": "{{bufferMemory_0.data.instance}}",

packages/server/marketplaces/chatflows/OpenAI Agent.json

@@ -208,7 +208,7 @@
                 "id": "openAIFunctionAgent_0",
                 "label": "OpenAI Function Agent",
                 "name": "openAIFunctionAgent",
-                "version": 3,
+                "version": 4,
                 "type": "AgentExecutor",
                 "baseClasses": ["AgentExecutor", "BaseChain"],
                 "category": "Agents",
@@ -243,9 +243,19 @@
                         "name": "model",
                         "type": "BaseChatModel",
                         "id": "openAIFunctionAgent_0-input-model-BaseChatModel"
+                    },
+                    {
+                        "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,
+                        "id": "openAIFunctionAgent_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "tools": ["{{calculator_0.data.instance}}", "{{serper_0.data.instance}}", "{{customTool_0.data.instance}}"],
                     "memory": "{{bufferMemory_0.data.instance}}",
                     "model": "{{chatOpenAI_0.data.instance}}",

packages/server/marketplaces/chatflows/ReAct Agent.json

@@ -52,7 +52,7 @@
             "data": {
                 "id": "mrklAgentChat_0",
                 "label": "ReAct Agent for Chat Models",
-                "version": 3,
+                "version": 4,
                 "name": "mrklAgentChat",
                 "type": "AgentExecutor",
                 "baseClasses": ["AgentExecutor", "BaseChain", "Runnable"],
@@ -78,9 +78,19 @@
                         "name": "memory",
                         "type": "BaseChatMemory",
                         "id": "mrklAgentChat_0-input-memory-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,
+                        "id": "mrklAgentChat_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "tools": ["{{calculator_1.data.instance}}", "{{serper_0.data.instance}}"],
                     "model": "{{chatOpenAI_0.data.instance}}",
                     "memory": "{{RedisBackedChatMemory_0.data.instance}}"

packages/server/marketplaces/chatflows/SQL DB Chain.json

@@ -249,7 +249,7 @@
             "data": {
                 "id": "sqlDatabaseChain_0",
                 "label": "Sql Database Chain",
-                "version": 4,
+                "version": 5,
                 "name": "sqlDatabaseChain",
                 "type": "SqlDatabaseChain",
                 "baseClasses": ["SqlDatabaseChain", "BaseChain", "Runnable"],
@@ -347,9 +347,19 @@
                         "name": "model",
                         "type": "BaseLanguageModel",
                         "id": "sqlDatabaseChain_0-input-model-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,
+                        "id": "sqlDatabaseChain_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "model": "{{chatOpenAI_0.data.instance}}",
                     "database": "sqlite",
                     "url": "",

packages/server/marketplaces/chatflows/Vectara RAG Chain.json

@@ -15,7 +15,7 @@
             "data": {
                 "id": "vectaraQAChain_0",
                 "label": "Vectara QA Chain",
-                "version": 1,
+                "version": 2,
                 "name": "vectaraQAChain",
                 "type": "VectaraQAChain",
                 "baseClasses": ["VectaraQAChain", "BaseChain", "Runnable"],
@@ -189,9 +189,19 @@
                         "name": "vectaraStore",
                         "type": "VectorStore",
                         "id": "vectaraQAChain_0-input-vectaraStore-VectorStore"
+                    },
+                    {
+                        "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,
+                        "id": "vectaraQAChain_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "vectaraStore": "{{vectara_1.data.instance}}",
                     "summarizerPromptName": "vectara-experimental-summary-ext-2023-10-23-small",
                     "responseLang": "eng",

packages/server/marketplaces/chatflows/WebBrowser.json

@@ -702,7 +702,7 @@
             "data": {
                 "id": "conversationalAgent_0",
                 "label": "Conversational Agent",
-                "version": 2,
+                "version": 3,
                 "name": "conversationalAgent",
                 "type": "AgentExecutor",
                 "baseClasses": ["AgentExecutor", "BaseChain", "Runnable"],
@@ -739,9 +739,19 @@
                         "name": "memory",
                         "type": "BaseChatMemory",
                         "id": "conversationalAgent_0-input-memory-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,
+                        "id": "conversationalAgent_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "tools": ["{{webBrowser_0.data.instance}}"],
                     "model": "{{chatOpenAI_1.data.instance}}",
                     "memory": "{{bufferMemory_0.data.instance}}",

packages/server/marketplaces/chatflows/WebPage QnA.json

@@ -187,7 +187,7 @@
             "data": {
                 "id": "conversationalRetrievalQAChain_0",
                 "label": "Conversational Retrieval QA Chain",
-                "version": 2,
+                "version": 3,
                 "name": "conversationalRetrievalQAChain",
                 "type": "ConversationalRetrievalQAChain",
                 "baseClasses": ["ConversationalRetrievalQAChain", "BaseChain", "Runnable"],
@@ -246,9 +246,19 @@
                         "optional": true,
                         "description": "If left empty, a default BufferMemory will be used",
                         "id": "conversationalRetrievalQAChain_0-input-memory-BaseMemory"
+                    },
+                    {
+                        "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,
+                        "id": "conversationalRetrievalQAChain_0-input-inputModeration-Moderation"
                     }
                 ],
                 "inputs": {
+                    "inputModeration": "",
                     "model": "{{chatOpenAI_0.data.instance}}",
                     "vectorStoreRetriever": "{{pinecone_0.data.instance}}",
                     "memory": "{{RedisBackedChatMemory_0.data.instance}}",