mirror of
https://github.com/farcasclaudiu/Flowise.git
synced 2026-06-22 09:01:09 +03:00
Chore/Update langchain version, openai, mistral, vertex, anthropic (#2180)
* update langchain version, openai, mistral, vertex, anthropic, introduced toolagent * upgrade @google/generative-ai 0.7.0, replicate and faiss-node * update cohere ver * adding chatCohere to streaming * update gemini to have image upload * update google genai, remove aiplugin
This commit is contained in:
Henry Heng
@@ -0,0 +1,260 @@
|
||||
import { flatten } from 'lodash'
|
||||
import { BaseMessage } from '@langchain/core/messages'
|
||||
import { ChainValues } from '@langchain/core/utils/types'
|
||||
import { RunnableSequence } from '@langchain/core/runnables'
|
||||
import { BaseChatModel } from '@langchain/core/language_models/chat_models'
|
||||
import { ChatPromptTemplate, MessagesPlaceholder, HumanMessagePromptTemplate, PromptTemplate } from '@langchain/core/prompts'
|
||||
import { formatToOpenAIToolMessages } from 'langchain/agents/format_scratchpad/openai_tools'
|
||||
import { type ToolsAgentStep } from 'langchain/agents/openai/output_parser'
|
||||
import { getBaseClasses } from '../../../src/utils'
|
||||
import { FlowiseMemory, ICommonObject, INode, INodeData, INodeParams, IUsedTool, IVisionChatModal } from '../../../src/Interface'
|
||||
import { ConsoleCallbackHandler, CustomChainHandler, additionalCallbacks } from '../../../src/handler'
|
||||
import { AgentExecutor, ToolCallingAgentOutputParser } from '../../../src/agents'
|
||||
import { Moderation, checkInputs, streamResponse } from '../../moderation/Moderation'
|
||||
import { formatResponse } from '../../outputparsers/OutputParserHelpers'
|
||||
import { addImagesToMessages, llmSupportsVision } from '../../../src/multiModalUtils'
|
||||
|
||||
class ToolAgent_Agents implements INode {
|
||||
label: string
|
||||
name: string
|
||||
version: number
|
||||
description: string
|
||||
type: string
|
||||
icon: string
|
||||
category: string
|
||||
baseClasses: string[]
|
||||
inputs: INodeParams[]
|
||||
sessionId?: string
|
||||
badge?: string
|
||||
|
||||
constructor(fields?: { sessionId?: string }) {
|
||||
this.label = 'Tool Agent'
|
||||
this.name = 'toolAgent'
|
||||
this.version = 1.0
|
||||
this.type = 'AgentExecutor'
|
||||
this.category = 'Agents'
|
||||
this.icon = 'toolAgent.png'
|
||||
this.description = `Agent that uses Function Calling to pick the tools and args to call`
|
||||
this.baseClasses = [this.type, ...getBaseClasses(AgentExecutor)]
|
||||
this.badge = 'NEW'
|
||||
this.inputs = [
|
||||
{
|
||||
label: 'Tools',
|
||||
name: 'tools',
|
||||
type: 'Tool',
|
||||
list: true
|
||||
},
|
||||
{
|
||||
label: 'Memory',
|
||||
name: 'memory',
|
||||
type: 'BaseChatMemory'
|
||||
},
|
||||
{
|
||||
label: 'Tool Calling Chat Model',
|
||||
name: 'model',
|
||||
type: 'BaseChatModel',
|
||||
description:
|
||||
'Only compatible with models that are capable of function calling. ChatOpenAI, ChatMistral, ChatAnthropic, ChatVertexAI'
|
||||
},
|
||||
{
|
||||
label: 'System Message',
|
||||
name: 'systemMessage',
|
||||
type: 'string',
|
||||
default: `You are a helpful AI assistant.`,
|
||||
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
|
||||
},
|
||||
{
|
||||
label: 'Max Iterations',
|
||||
name: 'maxIterations',
|
||||
type: 'number',
|
||||
optional: true,
|
||||
additionalParams: true
|
||||
}
|
||||
]
|
||||
this.sessionId = fields?.sessionId
|
||||
}
|
||||
|
||||
async init(nodeData: INodeData, input: string, options: ICommonObject): Promise<any> {
|
||||
return prepareAgent(nodeData, options, { sessionId: this.sessionId, chatId: options.chatId, input })
|
||||
}
|
||||
|
||||
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[]
|
||||
|
||||
const isStreamable = options.socketIO && options.socketIOClientId
|
||||
|
||||
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))
|
||||
if (isStreamable)
|
||||
streamResponse(options.socketIO && options.socketIOClientId, e.message, options.socketIO, options.socketIOClientId)
|
||||
return formatResponse(e.message)
|
||||
}
|
||||
}
|
||||
|
||||
const executor = prepareAgent(nodeData, options, { sessionId: this.sessionId, chatId: options.chatId, input })
|
||||
|
||||
const loggerHandler = new ConsoleCallbackHandler(options.logger)
|
||||
const callbacks = await additionalCallbacks(nodeData, options)
|
||||
|
||||
let res: ChainValues = {}
|
||||
let sourceDocuments: ICommonObject[] = []
|
||||
let usedTools: IUsedTool[] = []
|
||||
|
||||
if (isStreamable) {
|
||||
const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId)
|
||||
res = await executor.invoke({ input }, { callbacks: [loggerHandler, handler, ...callbacks] })
|
||||
if (res.sourceDocuments) {
|
||||
options.socketIO.to(options.socketIOClientId).emit('sourceDocuments', flatten(res.sourceDocuments))
|
||||
sourceDocuments = res.sourceDocuments
|
||||
}
|
||||
if (res.usedTools) {
|
||||
options.socketIO.to(options.socketIOClientId).emit('usedTools', res.usedTools)
|
||||
usedTools = res.usedTools
|
||||
}
|
||||
} else {
|
||||
res = await executor.invoke({ input }, { callbacks: [loggerHandler, ...callbacks] })
|
||||
if (res.sourceDocuments) {
|
||||
sourceDocuments = res.sourceDocuments
|
||||
}
|
||||
if (res.usedTools) {
|
||||
usedTools = res.usedTools
|
||||
}
|
||||
}
|
||||
|
||||
let output = res?.output as string
|
||||
|
||||
// Claude 3 Opus tends to spit out <thinking>..</thinking> as well, discard that in final output
|
||||
const regexPattern: RegExp = /<thinking>[\s\S]*?<\/thinking>/
|
||||
const matches: RegExpMatchArray | null = output.match(regexPattern)
|
||||
if (matches) {
|
||||
for (const match of matches) {
|
||||
output = output.replace(match, '')
|
||||
}
|
||||
}
|
||||
|
||||
await memory.addChatMessages(
|
||||
[
|
||||
{
|
||||
text: input,
|
||||
type: 'userMessage'
|
||||
},
|
||||
{
|
||||
text: output,
|
||||
type: 'apiMessage'
|
||||
}
|
||||
],
|
||||
this.sessionId
|
||||
)
|
||||
|
||||
let finalRes = output
|
||||
|
||||
if (sourceDocuments.length || usedTools.length) {
|
||||
const finalRes: ICommonObject = { text: output }
|
||||
if (sourceDocuments.length) {
|
||||
finalRes.sourceDocuments = flatten(sourceDocuments)
|
||||
}
|
||||
if (usedTools.length) {
|
||||
finalRes.usedTools = usedTools
|
||||
}
|
||||
return finalRes
|
||||
}
|
||||
|
||||
return finalRes
|
||||
}
|
||||
}
|
||||
|
||||
const prepareAgent = (nodeData: INodeData, options: ICommonObject, flowObj: { sessionId?: string; chatId?: string; input?: string }) => {
|
||||
const model = nodeData.inputs?.model as BaseChatModel
|
||||
const maxIterations = nodeData.inputs?.maxIterations as string
|
||||
const memory = nodeData.inputs?.memory as FlowiseMemory
|
||||
const systemMessage = nodeData.inputs?.systemMessage as string
|
||||
let tools = nodeData.inputs?.tools
|
||||
tools = flatten(tools)
|
||||
const memoryKey = memory.memoryKey ? memory.memoryKey : 'chat_history'
|
||||
const inputKey = memory.inputKey ? memory.inputKey : 'input'
|
||||
|
||||
const prompt = ChatPromptTemplate.fromMessages([
|
||||
['system', systemMessage],
|
||||
new MessagesPlaceholder(memoryKey),
|
||||
['human', `{${inputKey}}`],
|
||||
new MessagesPlaceholder('agent_scratchpad')
|
||||
])
|
||||
|
||||
if (llmSupportsVision(model)) {
|
||||
const visionChatModel = model as IVisionChatModal
|
||||
const messageContent = addImagesToMessages(nodeData, options, model.multiModalOption)
|
||||
|
||||
if (messageContent?.length) {
|
||||
visionChatModel.setVisionModel()
|
||||
|
||||
// Pop the `agent_scratchpad` MessagePlaceHolder
|
||||
let messagePlaceholder = prompt.promptMessages.pop() as MessagesPlaceholder
|
||||
if (prompt.promptMessages.at(-1) instanceof HumanMessagePromptTemplate) {
|
||||
const lastMessage = prompt.promptMessages.pop() as HumanMessagePromptTemplate
|
||||
const template = (lastMessage.prompt as PromptTemplate).template as string
|
||||
const msg = HumanMessagePromptTemplate.fromTemplate([
|
||||
...messageContent,
|
||||
{
|
||||
text: template
|
||||
}
|
||||
])
|
||||
msg.inputVariables = lastMessage.inputVariables
|
||||
prompt.promptMessages.push(msg)
|
||||
}
|
||||
|
||||
// Add the `agent_scratchpad` MessagePlaceHolder back
|
||||
prompt.promptMessages.push(messagePlaceholder)
|
||||
} else {
|
||||
visionChatModel.revertToOriginalModel()
|
||||
}
|
||||
}
|
||||
|
||||
if (model.bindTools === undefined) {
|
||||
throw new Error(`This agent requires that the "bindTools()" method be implemented on the input model.`)
|
||||
}
|
||||
|
||||
const modelWithTools = model.bindTools(tools)
|
||||
|
||||
const runnableAgent = RunnableSequence.from([
|
||||
{
|
||||
[inputKey]: (i: { input: string; steps: ToolsAgentStep[] }) => i.input,
|
||||
agent_scratchpad: (i: { input: string; steps: ToolsAgentStep[] }) => formatToOpenAIToolMessages(i.steps),
|
||||
[memoryKey]: async (_: { input: string; steps: ToolsAgentStep[] }) => {
|
||||
const messages = (await memory.getChatMessages(flowObj?.sessionId, true)) as BaseMessage[]
|
||||
return messages ?? []
|
||||
}
|
||||
},
|
||||
prompt,
|
||||
modelWithTools,
|
||||
new ToolCallingAgentOutputParser()
|
||||
])
|
||||
|
||||
const executor = AgentExecutor.fromAgentAndTools({
|
||||
agent: runnableAgent,
|
||||
tools,
|
||||
sessionId: flowObj?.sessionId,
|
||||
chatId: flowObj?.chatId,
|
||||
input: flowObj?.input,
|
||||
verbose: process.env.DEBUG === 'true' ? true : false,
|
||||
maxIterations: maxIterations ? parseFloat(maxIterations) : undefined
|
||||
})
|
||||
|
||||
return executor
|
||||
}
|
||||
|
||||
module.exports = { nodeClass: ToolAgent_Agents }
|
||||
Reference in New Issue
Block a user