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change agent/chain with memory to use runnable

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This commit is contained in:
Henry
2024-01-08 13:02:56 +00:00
parent d5b8db5599
commit 02482f1b38
38 changed files with 1752 additions and 1394 deletions
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packages/components/nodes/agents/ConversationalRetrievalAgent/ConversationalRetrievalAgent.ts
+87 -40
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@@ -1,9 +1,14 @@
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { initializeAgentExecutorWithOptions, AgentExecutor } from 'langchain/agents'
import { getBaseClasses, mapChatHistory } from '../../../src/utils'
import { ChainValues, AgentStep, BaseMessage } from 'langchain/schema'
import { flatten } from 'lodash'
import { BaseChatMemory } from 'langchain/memory'
import { ChatOpenAI } from 'langchain/chat_models/openai'
import { ChatPromptTemplate, MessagesPlaceholder } from 'langchain/prompts'
import { formatToOpenAIFunction } from 'langchain/tools'
import { RunnableSequence } from 'langchain/schema/runnable'
import { FlowiseMemory, ICommonObject, IMessage, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses } from '../../../src/utils'
import { ConsoleCallbackHandler, CustomChainHandler, additionalCallbacks } from '../../../src/handler'
import { OpenAIFunctionsAgentOutputParser } from 'langchain/agents/openai/output_parser'
import { AgentExecutor, formatAgentSteps } from '../../../src/agents'
const defaultMessage = `Do your best to answer the questions. Feel free to use any tools available to look up relevant information, only if necessary.`
@@ -17,8 +22,9 @@ class ConversationalRetrievalAgent_Agents implements INode {
category: string
baseClasses: string[]
inputs: INodeParams[]
sessionId?: string
constructor() {
constructor(fields?: { sessionId?: string }) {
this.label = 'Conversational Retrieval Agent'
this.name = 'conversationalRetrievalAgent'
this.version = 3.0
@@ -54,55 +60,96 @@ class ConversationalRetrievalAgent_Agents implements INode {
additionalParams: true
}
]
this.sessionId = fields?.sessionId
}
async init(nodeData: INodeData): Promise<any> {
const model = nodeData.inputs?.model
const memory = nodeData.inputs?.memory as BaseChatMemory
const systemMessage = nodeData.inputs?.systemMessage as string
let tools = nodeData.inputs?.tools
tools = flatten(tools)
const executor = await initializeAgentExecutorWithOptions(tools, model, {
agentType: 'openai-functions',
verbose: process.env.DEBUG === 'true' ? true : false,
agentArgs: {
prefix: systemMessage ?? defaultMessage
},
returnIntermediateSteps: true
})
executor.memory = memory
return executor
async init(nodeData: INodeData, input: string, options: ICommonObject): Promise<any> {
return prepareAgent(nodeData, { sessionId: this.sessionId, chatId: options.chatId, input }, options.chatHistory)
}
async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
const executor = nodeData.instance as AgentExecutor
if (executor.memory) {
;(executor.memory as any).memoryKey = 'chat_history'
;(executor.memory as any).outputKey = 'output'
;(executor.memory as any).returnMessages = true
const chatHistoryClassName = (executor.memory as any).chatHistory.constructor.name
// Only replace when its In-Memory
if (chatHistoryClassName && chatHistoryClassName === 'ChatMessageHistory') {
;(executor.memory as any).chatHistory = mapChatHistory(options)
}
}
const memory = nodeData.inputs?.memory as FlowiseMemory
const executor = prepareAgent(nodeData, { sessionId: this.sessionId, chatId: options.chatId, input }, options.chatHistory)
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const callbacks = await additionalCallbacks(nodeData, options)
let res: ChainValues = {}
if (options.socketIO && options.socketIOClientId) {
const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId)
const result = await executor.call({ input }, [loggerHandler, handler, ...callbacks])
return result?.output
res = await executor.invoke({ input }, { callbacks: [loggerHandler, handler, ...callbacks] })
} else {
const result = await executor.call({ input }, [loggerHandler, ...callbacks])
return result?.output
res = await executor.invoke({ input }, { callbacks: [loggerHandler, ...callbacks] })
}
await memory.addChatMessages(
[
{
text: input,
type: 'userMessage'
},
{
text: res?.output,
type: 'apiMessage'
}
],
this.sessionId
)
return res?.output
}
}
const prepareAgent = (
nodeData: INodeData,
flowObj: { sessionId?: string; chatId?: string; input?: string },
chatHistory: IMessage[] = []
) => {
const model = nodeData.inputs?.model as ChatOpenAI
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([
['ai', systemMessage ? systemMessage : defaultMessage],
new MessagesPlaceholder(memoryKey),
['human', `{${inputKey}}`],
new MessagesPlaceholder('agent_scratchpad')
])
const modelWithFunctions = model.bind({
functions: [...tools.map((tool: any) => formatToOpenAIFunction(tool))]
})
const runnableAgent = RunnableSequence.from([
{
[inputKey]: (i: { input: string; steps: AgentStep[] }) => i.input,
agent_scratchpad: (i: { input: string; steps: AgentStep[] }) => formatAgentSteps(i.steps),
[memoryKey]: async (_: { input: string; steps: AgentStep[] }) => {
const messages = (await memory.getChatMessages(flowObj?.sessionId, true, chatHistory)) as BaseMessage[]
return messages ?? []
}
},
prompt,
modelWithFunctions,
new OpenAIFunctionsAgentOutputParser()
])
const executor = AgentExecutor.fromAgentAndTools({
agent: runnableAgent,
tools,
sessionId: flowObj?.sessionId,
chatId: flowObj?.chatId,
input: flowObj?.input,
returnIntermediateSteps: true,
verbose: process.env.DEBUG === 'true' ? true : false
})
return executor
}
module.exports = { nodeClass: ConversationalRetrievalAgent_Agents }