Merge pull request #147 from FlowiseAI/feature/ConversationChain
Feature/Add conversation chain
This commit is contained in:
Henry Heng
GitHub
commit
0fb16c7849
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import { ICommonObject, IMessage, INode, INodeData, INodeParams } from '../../../src/Interface'
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import { ConversationChain } from 'langchain/chains'
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import { getBaseClasses } from '../../../src/utils'
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import { ChatPromptTemplate, HumanMessagePromptTemplate, MessagesPlaceholder, SystemMessagePromptTemplate } from 'langchain/prompts'
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import { BufferMemory, ChatMessageHistory } from 'langchain/memory'
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import { BaseChatModel } from 'langchain/chat_models/base'
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import { AIChatMessage, HumanChatMessage } from 'langchain/schema'
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const 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.`
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class ConversationChain_Chains implements INode {
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label: string
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name: string
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type: string
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icon: string
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category: string
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baseClasses: string[]
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description: string
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inputs: INodeParams[]
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constructor() {
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this.label = 'Conversation Chain'
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this.name = 'conversationChain'
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this.type = 'ConversationChain'
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this.icon = 'chain.svg'
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this.category = 'Chains'
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this.description = 'Chat models specific conversational chain with memory'
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this.baseClasses = [this.type, ...getBaseClasses(ConversationChain)]
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this.inputs = [
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{
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label: 'Language Model',
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name: 'model',
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type: 'BaseChatModel'
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},
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{
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label: 'Memory',
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name: 'memory',
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type: 'BaseMemory'
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},
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{
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label: 'System Message',
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name: 'systemMessagePrompt',
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type: 'string',
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rows: 4,
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additionalParams: true,
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optional: true,
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placeholder: 'You are a helpful assistant that write codes'
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}
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]
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}
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async init(nodeData: INodeData): Promise<any> {
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const model = nodeData.inputs?.model as BaseChatModel
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const memory = nodeData.inputs?.memory as BufferMemory
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const prompt = nodeData.inputs?.systemMessagePrompt as string
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const obj: any = {
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llm: model,
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memory
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}
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const chatPrompt = ChatPromptTemplate.fromPromptMessages([
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SystemMessagePromptTemplate.fromTemplate(prompt ? `${prompt}\n${systemMessage}` : systemMessage),
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new MessagesPlaceholder(memory.memoryKey ?? 'chat_history'),
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HumanMessagePromptTemplate.fromTemplate('{input}')
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])
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obj.prompt = chatPrompt
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const chain = new ConversationChain(obj)
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return chain
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}
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async run(nodeData: INodeData, input: string, options: ICommonObject): Promise<string> {
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const chain = nodeData.instance as ConversationChain
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const memory = nodeData.inputs?.memory as BufferMemory
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if (options && options.chatHistory) {
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const chatHistory = []
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const histories: IMessage[] = options.chatHistory
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for (const message of histories) {
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if (message.type === 'apiMessage') {
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chatHistory.push(new AIChatMessage(message.message))
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} else if (message.type === 'userMessage') {
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chatHistory.push(new HumanChatMessage(message.message))
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}
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}
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memory.chatHistory = new ChatMessageHistory(chatHistory)
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chain.memory = memory
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}
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const res = await chain.call({ input })
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return res?.response
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}
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}
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module.exports = { nodeClass: ConversationChain_Chains }
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@ -0,0 +1,6 @@
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<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-dna" width="24" height="24" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round">
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<path stroke="none" d="M0 0h24v24H0z" fill="none"></path>
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<path d="M14.828 14.828a4 4 0 1 0 -5.656 -5.656a4 4 0 0 0 5.656 5.656z"></path>
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<path d="M9.172 20.485a4 4 0 1 0 -5.657 -5.657"></path>
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<path d="M14.828 3.515a4 4 0 0 0 5.657 5.657"></path>
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</svg>
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After Width: | Height: | Size: 489 B |
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@ -0,0 +1,282 @@
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{
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"description": "Basic example of Conversation Chain with built-in memory - works exactly like ChatGPT",
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"nodes": [
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{
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"width": 300,
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"height": 524,
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"id": "chatOpenAI_0",
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"position": {
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"x": 750.6529856117049,
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"y": -75.72544375812092
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},
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"type": "customNode",
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"data": {
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"id": "chatOpenAI_0",
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"label": "ChatOpenAI",
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"name": "chatOpenAI",
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"type": "ChatOpenAI",
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"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel", "BaseLangChain"],
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"category": "Chat Models",
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"description": "Wrapper around OpenAI large language models that use the Chat endpoint",
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"inputParams": [
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{
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"label": "OpenAI Api Key",
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"name": "openAIApiKey",
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"type": "password",
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"id": "chatOpenAI_0-input-openAIApiKey-password"
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},
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{
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"label": "Model Name",
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"name": "modelName",
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"type": "options",
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"options": [
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{
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"label": "gpt-4",
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"name": "gpt-4"
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},
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{
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"label": "gpt-4-0314",
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"name": "gpt-4-0314"
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},
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{
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"label": "gpt-4-32k-0314",
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"name": "gpt-4-32k-0314"
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},
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{
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"label": "gpt-3.5-turbo",
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"name": "gpt-3.5-turbo"
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},
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{
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"label": "gpt-3.5-turbo-0301",
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"name": "gpt-3.5-turbo-0301"
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}
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],
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"default": "gpt-3.5-turbo",
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"optional": true,
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"id": "chatOpenAI_0-input-modelName-options"
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},
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{
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"label": "Temperature",
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"name": "temperature",
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"type": "number",
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"default": 0.9,
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"optional": true,
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"id": "chatOpenAI_0-input-temperature-number"
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},
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{
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"label": "Max Tokens",
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"name": "maxTokens",
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"type": "number",
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"optional": true,
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"additionalParams": true,
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"id": "chatOpenAI_0-input-maxTokens-number"
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},
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{
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"label": "Top Probability",
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"name": "topP",
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"type": "number",
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"optional": true,
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"additionalParams": true,
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"id": "chatOpenAI_0-input-topP-number"
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},
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{
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"label": "Frequency Penalty",
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"name": "frequencyPenalty",
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"type": "number",
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"optional": true,
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"additionalParams": true,
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"id": "chatOpenAI_0-input-frequencyPenalty-number"
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},
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{
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"label": "Presence Penalty",
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"name": "presencePenalty",
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"type": "number",
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"optional": true,
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"additionalParams": true,
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"id": "chatOpenAI_0-input-presencePenalty-number"
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},
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{
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"label": "Timeout",
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"name": "timeout",
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"type": "number",
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"optional": true,
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"additionalParams": true,
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"id": "chatOpenAI_0-input-timeout-number"
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}
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],
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"inputAnchors": [],
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"inputs": {
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"modelName": "gpt-3.5-turbo",
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"temperature": 0.9,
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"maxTokens": "",
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"topP": "",
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"frequencyPenalty": "",
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"presencePenalty": "",
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"timeout": ""
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},
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"outputAnchors": [
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{
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"id": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|BaseLangChain",
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"name": "chatOpenAI",
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"label": "ChatOpenAI",
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"type": "ChatOpenAI | BaseChatModel | BaseLanguageModel | BaseLangChain"
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}
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],
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"outputs": {},
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"selected": false
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},
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"positionAbsolute": {
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"x": 750.6529856117049,
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"y": -75.72544375812092
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},
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"selected": false,
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"dragging": false
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},
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{
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"width": 300,
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"height": 376,
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"id": "bufferMemory_0",
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"position": {
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"x": 753.4300788823234,
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"y": 479.5336426526603
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},
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"type": "customNode",
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"data": {
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"id": "bufferMemory_0",
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"label": "Buffer Memory",
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"name": "bufferMemory",
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"type": "BufferMemory",
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"baseClasses": ["BufferMemory", "BaseChatMemory", "BaseMemory"],
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"category": "Memory",
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"description": "Remembers previous conversational back and forths directly",
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"inputParams": [
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{
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"label": "Memory Key",
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"name": "memoryKey",
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"type": "string",
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"default": "chat_history",
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"id": "bufferMemory_0-input-memoryKey-string"
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},
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{
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"label": "Input Key",
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"name": "inputKey",
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"type": "string",
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"default": "input",
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"id": "bufferMemory_0-input-inputKey-string"
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}
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],
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"inputAnchors": [],
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"inputs": {
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"memoryKey": "chat_history",
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"inputKey": "input"
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},
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"outputAnchors": [
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{
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"id": "bufferMemory_0-output-bufferMemory-BufferMemory|BaseChatMemory|BaseMemory",
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"name": "bufferMemory",
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"label": "BufferMemory",
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"type": "BufferMemory | BaseChatMemory | BaseMemory"
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}
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],
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"outputs": {},
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"selected": false
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},
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"selected": false,
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"positionAbsolute": {
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"x": 753.4300788823234,
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"y": 479.5336426526603
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},
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"dragging": false
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},
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{
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"width": 300,
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"height": 332,
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"id": "conversationChain_0",
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"position": {
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"x": 1201.6630991237407,
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"y": 291.86981791303066
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},
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"type": "customNode",
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"data": {
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"id": "conversationChain_0",
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"label": "Conversation Chain",
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"name": "conversationChain",
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"type": "ConversationChain",
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"baseClasses": ["ConversationChain", "LLMChain", "BaseChain", "BaseLangChain"],
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"category": "Chains",
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"description": "Chat models specific conversational chain with memory",
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"inputParams": [
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{
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"label": "System Message",
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"name": "systemMessagePrompt",
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"type": "string",
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"rows": 4,
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"additionalParams": true,
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"optional": true,
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"placeholder": "You are a helpful assistant that write codes",
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"id": "conversationChain_0-input-systemMessagePrompt-string"
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}
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],
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"inputAnchors": [
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{
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"label": "Language Model",
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"name": "model",
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"type": "BaseChatModel",
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"id": "conversationChain_0-input-model-BaseChatModel"
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},
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{
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"label": "Memory",
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"name": "memory",
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"type": "BaseMemory",
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"id": "conversationChain_0-input-memory-BaseMemory"
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}
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],
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"inputs": {
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"model": "{{chatOpenAI_0.data.instance}}",
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"memory": "{{bufferMemory_0.data.instance}}",
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"systemMessagePrompt": ""
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},
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"outputAnchors": [
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{
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"id": "conversationChain_0-output-conversationChain-ConversationChain|LLMChain|BaseChain|BaseLangChain",
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"name": "conversationChain",
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"label": "ConversationChain",
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"type": "ConversationChain | LLMChain | BaseChain | BaseLangChain"
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}
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],
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"outputs": {},
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"selected": false
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},
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"selected": false,
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"positionAbsolute": {
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"x": 1201.6630991237407,
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"y": 291.86981791303066
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},
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"dragging": false
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}
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],
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"edges": [
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{
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"source": "chatOpenAI_0",
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"sourceHandle": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|BaseLangChain",
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"target": "conversationChain_0",
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"targetHandle": "conversationChain_0-input-model-BaseChatModel",
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"type": "buttonedge",
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"id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|BaseLangChain-conversationChain_0-conversationChain_0-input-model-BaseChatModel",
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"data": {
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"label": ""
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}
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},
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{
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"source": "bufferMemory_0",
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"sourceHandle": "bufferMemory_0-output-bufferMemory-BufferMemory|BaseChatMemory|BaseMemory",
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"target": "conversationChain_0",
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"targetHandle": "conversationChain_0-input-memory-BaseMemory",
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"type": "buttonedge",
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"id": "bufferMemory_0-bufferMemory_0-output-bufferMemory-BufferMemory|BaseChatMemory|BaseMemory-conversationChain_0-conversationChain_0-input-memory-BaseMemory",
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"data": {
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"label": ""
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}
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}
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]
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}
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@ -1,5 +1,5 @@
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{
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"description": "Basic example of LLM Chain with a Prompt Template and LLM Model",
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"description": "Basic example of stateless (no memory) LLM Chain with a Prompt Template and LLM Model",
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"nodes": [
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{
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"width": 300,
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