farcasclaudiu/Flowise
1
0
Fork 0
mirror of https://github.com/farcasclaudiu/Flowise.git synced 2026-06-28 15:00:57 +03:00
Code Issues Packages Projects Releases Wiki Activity

Add input moderation for all chains and agents

Browse Source
This commit is contained in:
Octavian FlowiseAI
2024-03-09 23:19:39 +01:00
parent 6eab5cf681
commit 69e082e29f
41 changed files with 711 additions and 61 deletions
Download Patch File Download Diff File Expand all files Collapse all files
packages/components/nodes/agents/AirtableAgent/AirtableAgent.ts
+24 -2
View File
@@ -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
+24 -2
View File
@@ -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
+25 -2
View File
@@ -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
+24 -2
View File
@@ -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
+23 -2
View File
@@ -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
+25 -2
View File
@@ -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
+24 -2
View File
@@ -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
+25 -2
View File
@@ -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
+24 -1
View File
@@ -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
+23 -2
View File
@@ -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
+23 -3
View File
@@ -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
+22 -1
View File
@@ -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
+23 -2
View File
@@ -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
+22 -2
View File
@@ -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
+23 -2
View File
@@ -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
+23 -2
View File
@@ -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
+24 -2
View File
@@ -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
+24 -2
View File
@@ -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
}