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add console call back to chains

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This commit is contained in:
Henry
2024-01-19 18:36:49 +00:00
parent 6b369d4ab9
commit 2b2a5b9028
4 changed files with 446 additions and 330 deletions
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packages/components/nodes/chains/ConversationChain/ConversationChain.ts
+58 -28
View File
@@ -1,13 +1,12 @@
import { FlowiseMemory, ICommonObject, IMessage, INode, INodeData, INodeParams } from '../../../src/Interface'
import { ConversationChain } from 'langchain/chains'
import { getBaseClasses } from '../../../src/utils'
import { getBaseClasses, handleEscapeCharacters } from '../../../src/utils'
import { ChatPromptTemplate, HumanMessagePromptTemplate, MessagesPlaceholder, SystemMessagePromptTemplate } from 'langchain/prompts'
import { BaseChatModel } from 'langchain/chat_models/base'
import { ConsoleCallbackHandler, CustomChainHandler, additionalCallbacks } from '../../../src/handler'
import { flatten } from 'lodash'
import { Document } from 'langchain/document'
import { RunnableSequence } from 'langchain/schema/runnable'
import { StringOutputParser } from 'langchain/schema/output_parser'
import { ConsoleCallbackHandler as LCConsoleCallbackHandler } from '@langchain/core/tracers/console'
let systemMessage = `The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.`
const inputKey = 'input'
@@ -27,7 +26,7 @@ class ConversationChain_Chains implements INode {
constructor(fields?: { sessionId?: string }) {
this.label = 'Conversation Chain'
this.name = 'conversationChain'
this.version = 1.0
this.version = 2.0
this.type = 'ConversationChain'
this.icon = 'conv.svg'
this.category = 'Chains'
@@ -44,6 +43,14 @@ class ConversationChain_Chains implements INode {
name: 'memory',
type: 'BaseMemory'
},
{
label: 'Chat Prompt Template',
name: 'chatPromptTemplate',
type: 'ChatPromptTemplate',
description: 'Override existing prompt with Chat Prompt Template. Human Message must includes {input} variable',
optional: true
},
/* Deprecated
{
label: 'Document',
name: 'document',
@@ -52,15 +59,17 @@ class ConversationChain_Chains implements INode {
'Include whole document into the context window, if you get maximum context length error, please use model with higher context window like Claude 100k, or gpt4 32k',
optional: true,
list: true
},
},*/
{
label: 'System Message',
name: 'systemMessagePrompt',
type: 'string',
rows: 4,
description: 'If Chat Prompt Template is provided, this will be ignored',
additionalParams: true,
optional: true,
placeholder: 'You are a helpful assistant that write codes'
default: systemMessage,
placeholder: systemMessage
}
]
this.sessionId = fields?.sessionId
@@ -76,15 +85,21 @@ class ConversationChain_Chains implements INode {
const chain = prepareChain(nodeData, this.sessionId, options.chatHistory)
const loggerHandler = new ConsoleCallbackHandler(options.logger)
const callbacks = await additionalCallbacks(nodeData, options)
const additionalCallback = await additionalCallbacks(nodeData, options)
let res = ''
let callbacks = [loggerHandler, ...additionalCallback]
if (process.env.DEBUG === 'true') {
callbacks.push(new LCConsoleCallbackHandler())
}
if (options.socketIO && options.socketIOClientId) {
const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId)
res = await chain.invoke({ input }, { callbacks: [loggerHandler, handler, ...callbacks] })
callbacks.push(handler)
res = await chain.invoke({ input }, { callbacks })
} else {
res = await chain.invoke({ input }, { callbacks: [loggerHandler, ...callbacks] })
res = await chain.invoke({ input }, { callbacks })
}
await memory.addChatMessages(
@@ -108,28 +123,27 @@ class ConversationChain_Chains implements INode {
const prepareChatPrompt = (nodeData: INodeData) => {
const memory = nodeData.inputs?.memory as FlowiseMemory
const prompt = nodeData.inputs?.systemMessagePrompt as string
const docs = nodeData.inputs?.document as Document[]
const chatPromptTemplate = nodeData.inputs?.chatPromptTemplate as ChatPromptTemplate
const flattenDocs = docs && docs.length ? flatten(docs) : []
const finalDocs = []
for (let i = 0; i < flattenDocs.length; i += 1) {
if (flattenDocs[i] && flattenDocs[i].pageContent) {
finalDocs.push(new Document(flattenDocs[i]))
if (chatPromptTemplate && chatPromptTemplate.promptMessages.length) {
const sysPrompt = chatPromptTemplate.promptMessages[0]
const humanPrompt = chatPromptTemplate.promptMessages[chatPromptTemplate.promptMessages.length - 1]
const chatPrompt = ChatPromptTemplate.fromMessages([
sysPrompt,
new MessagesPlaceholder(memory.memoryKey ?? 'chat_history'),
humanPrompt
])
if ((chatPromptTemplate as any).promptValues) {
// @ts-ignore
chatPrompt.promptValues = (chatPromptTemplate as any).promptValues
}
return chatPrompt
}
let finalText = ''
for (let i = 0; i < finalDocs.length; i += 1) {
finalText += finalDocs[i].pageContent
}
const replaceChar: string[] = ['{', '}']
for (const char of replaceChar) finalText = finalText.replaceAll(char, '')
if (finalText) systemMessage = `${systemMessage}\nThe AI has the following context:\n${finalText}`
const chatPrompt = ChatPromptTemplate.fromMessages([
SystemMessagePromptTemplate.fromTemplate(prompt ? `${prompt}\n${systemMessage}` : systemMessage),
SystemMessagePromptTemplate.fromTemplate(prompt ? prompt : systemMessage),
new MessagesPlaceholder(memory.memoryKey ?? 'chat_history'),
HumanMessagePromptTemplate.fromTemplate(`{${inputKey}}`)
])
@@ -142,15 +156,31 @@ const prepareChain = (nodeData: INodeData, sessionId?: string, chatHistory: IMes
const memory = nodeData.inputs?.memory as FlowiseMemory
const memoryKey = memory.memoryKey ?? 'chat_history'
const chatPrompt = prepareChatPrompt(nodeData)
let promptVariables = {}
const promptValuesRaw = (chatPrompt as any).promptValues
if (promptValuesRaw) {
const promptValues = handleEscapeCharacters(promptValuesRaw, true)
for (const val in promptValues) {
promptVariables = {
...promptVariables,
[val]: () => {
return promptValues[val]
}
}
}
}
const conversationChain = RunnableSequence.from([
{
[inputKey]: (input: { input: string }) => input.input,
[memoryKey]: async () => {
const history = await memory.getChatMessages(sessionId, true, chatHistory)
return history
}
},
...promptVariables
},
prepareChatPrompt(nodeData),
chatPrompt,
model,
new StringOutputParser()
])