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Merge pull request #2 from FlowiseAI/feature/BabyAGI
Feature/Add BabyAGI node
This commit is contained in:
Henry Heng
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import { INode, INodeData, INodeParams } from '../../../src/Interface'
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import { BabyAGI } from './core'
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import { BaseChatModel } from 'langchain/chat_models'
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import { VectorStore } from 'langchain/vectorstores'
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class BabyAGI_Agents implements INode {
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label: string
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name: string
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description: 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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inputs: INodeParams[]
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constructor() {
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this.label = 'BabyAGI'
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this.name = 'babyAGI'
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this.type = 'BabyAGI'
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this.category = 'Agents'
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this.icon = 'babyagi.jpg'
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this.description = 'Task Driven Autonomous Agent which creates new task and reprioritizes task list based on objective'
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this.baseClasses = ['BabyAGI']
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this.inputs = [
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{
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label: 'Chat 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: 'Vector Store',
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name: 'vectorStore',
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type: 'VectorStore'
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},
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{
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label: 'Task Loop',
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name: 'taskLoop',
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type: 'number',
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default: 3
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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 vectorStore = nodeData.inputs?.vectorStore as VectorStore
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const taskLoop = nodeData.inputs?.taskLoop as string
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const babyAgi = BabyAGI.fromLLM(model, vectorStore, parseInt(taskLoop, 10))
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return babyAgi
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}
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async run(nodeData: INodeData, input: string): Promise<string> {
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const executor = nodeData.instance as BabyAGI
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const objective = input
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const res = await executor.call({ objective })
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return res
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}
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}
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module.exports = { nodeClass: BabyAGI_Agents }
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import { LLMChain } from 'langchain/chains'
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import { BaseChatModel } from 'langchain/chat_models'
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import { VectorStore } from 'langchain/dist/vectorstores/base'
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import { Document } from 'langchain/document'
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import { PromptTemplate } from 'langchain/prompts'
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class TaskCreationChain extends LLMChain {
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constructor(prompt: PromptTemplate, llm: BaseChatModel) {
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super({ prompt, llm })
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}
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static from_llm(llm: BaseChatModel): LLMChain {
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const taskCreationTemplate: string =
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'You are a task creation AI that uses the result of an execution agent' +
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' to create new tasks with the following objective: {objective},' +
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' The last completed task has the result: {result}.' +
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' This result was based on this task description: {task_description}.' +
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' These are incomplete tasks list: {incomplete_tasks}.' +
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' Based on the result, create new tasks to be completed' +
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' by the AI system that do not overlap with incomplete tasks.' +
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' Return the tasks as an array.'
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const prompt = new PromptTemplate({
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template: taskCreationTemplate,
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inputVariables: ['result', 'task_description', 'incomplete_tasks', 'objective']
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})
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return new TaskCreationChain(prompt, llm)
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}
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}
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class TaskPrioritizationChain extends LLMChain {
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constructor(prompt: PromptTemplate, llm: BaseChatModel) {
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super({ prompt, llm })
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}
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static from_llm(llm: BaseChatModel): TaskPrioritizationChain {
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const taskPrioritizationTemplate: string =
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'You are a task prioritization AI tasked with cleaning the formatting of and reprioritizing' +
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' the following task list: {task_names}.' +
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' Consider the ultimate objective of your team: {objective}.' +
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' Do not remove any tasks. Return the result as a numbered list, like:' +
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' #. First task' +
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' #. Second task' +
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' Start the task list with number {next_task_id}.'
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const prompt = new PromptTemplate({
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template: taskPrioritizationTemplate,
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inputVariables: ['task_names', 'next_task_id', 'objective']
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})
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return new TaskPrioritizationChain(prompt, llm)
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}
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}
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class ExecutionChain extends LLMChain {
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constructor(prompt: PromptTemplate, llm: BaseChatModel) {
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super({ prompt, llm })
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}
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static from_llm(llm: BaseChatModel): LLMChain {
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const executionTemplate: string =
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'You are an AI who performs one task based on the following objective: {objective}.' +
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' Take into account these previously completed tasks: {context}.' +
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' Your task: {task}.' +
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' Response:'
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const prompt = new PromptTemplate({
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template: executionTemplate,
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inputVariables: ['objective', 'context', 'task']
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})
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return new ExecutionChain(prompt, llm)
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}
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}
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async function getNextTask(
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taskCreationChain: LLMChain,
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result: string,
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taskDescription: string,
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taskList: string[],
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objective: string
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): Promise<any[]> {
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const incompleteTasks: string = taskList.join(', ')
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const response: string = await taskCreationChain.predict({
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result,
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task_description: taskDescription,
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incomplete_tasks: incompleteTasks,
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objective
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})
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const newTasks: string[] = response.split('\n')
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return newTasks.filter((taskName) => taskName.trim()).map((taskName) => ({ task_name: taskName }))
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}
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interface Task {
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task_id: number
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task_name: string
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}
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async function prioritizeTasks(
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taskPrioritizationChain: LLMChain,
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thisTaskId: number,
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taskList: Task[],
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objective: string
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): Promise<Task[]> {
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const next_task_id = thisTaskId + 1
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const task_names = taskList.map((t) => t.task_name).join(', ')
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const response = await taskPrioritizationChain.predict({ task_names, next_task_id, objective })
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const newTasks = response.split('\n')
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const prioritizedTaskList: Task[] = []
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for (const taskString of newTasks) {
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if (!taskString.trim()) {
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// eslint-disable-next-line no-continue
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continue
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}
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const taskParts = taskString.trim().split('. ', 2)
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if (taskParts.length === 2) {
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const task_id = parseInt(taskParts[0].trim(), 10)
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const task_name = taskParts[1].trim()
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prioritizedTaskList.push({ task_id, task_name })
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}
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}
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return prioritizedTaskList
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}
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export async function get_top_tasks(vectorStore: VectorStore, query: string, k: number): Promise<string[]> {
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const docs = await vectorStore.similaritySearch(query, k)
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let returnDocs: string[] = []
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for (const doc of docs) {
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returnDocs.push(doc.metadata.task)
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}
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return returnDocs
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}
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async function executeTask(vectorStore: VectorStore, executionChain: LLMChain, objective: string, task: string, k = 5): Promise<string> {
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const context = await get_top_tasks(vectorStore, objective, k)
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return executionChain.predict({ objective, context, task })
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}
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export class BabyAGI {
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taskList: Array<Task> = []
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taskCreationChain: TaskCreationChain
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taskPrioritizationChain: TaskPrioritizationChain
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executionChain: ExecutionChain
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taskIdCounter = 1
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vectorStore: VectorStore
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maxIterations = 3
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constructor(
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taskCreationChain: TaskCreationChain,
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taskPrioritizationChain: TaskPrioritizationChain,
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executionChain: ExecutionChain,
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vectorStore: VectorStore,
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maxIterations: number
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) {
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this.taskCreationChain = taskCreationChain
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this.taskPrioritizationChain = taskPrioritizationChain
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this.executionChain = executionChain
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this.vectorStore = vectorStore
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this.maxIterations = maxIterations
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}
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addTask(task: Task) {
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this.taskList.push(task)
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}
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printTaskList() {
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// eslint-disable-next-line no-console
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console.log('\x1b[95m\x1b[1m\n*****TASK LIST*****\n\x1b[0m\x1b[0m')
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// eslint-disable-next-line no-console
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this.taskList.forEach((t) => console.log(`${t.task_id}: ${t.task_name}`))
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}
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printNextTask(task: Task) {
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// eslint-disable-next-line no-console
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console.log('\x1b[92m\x1b[1m\n*****NEXT TASK*****\n\x1b[0m\x1b[0m')
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// eslint-disable-next-line no-console
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console.log(`${task.task_id}: ${task.task_name}`)
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}
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printTaskResult(result: string) {
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// eslint-disable-next-line no-console
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console.log('\x1b[93m\x1b[1m\n*****TASK RESULT*****\n\x1b[0m\x1b[0m')
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// eslint-disable-next-line no-console
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console.log(result)
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}
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getInputKeys(): string[] {
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return ['objective']
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}
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getOutputKeys(): string[] {
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return []
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}
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async call(inputs: Record<string, any>): Promise<string> {
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const { objective } = inputs
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const firstTask = inputs.first_task || 'Make a todo list'
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this.addTask({ task_id: 1, task_name: firstTask })
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let numIters = 0
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let loop = true
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let finalResult = ''
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while (loop) {
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if (this.taskList.length) {
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this.printTaskList()
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// Step 1: Pull the first task
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const task = this.taskList.shift()
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if (!task) break
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this.printNextTask(task)
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// Step 2: Execute the task
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const result = await executeTask(this.vectorStore, this.executionChain, objective, task.task_name)
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const thisTaskId = task.task_id
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finalResult = result
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this.printTaskResult(result)
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// Step 3: Store the result in Pinecone
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const docs = new Document({ pageContent: result, metadata: { task: task.task_name } })
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this.vectorStore.addDocuments([docs])
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// Step 4: Create new tasks and reprioritize task list
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const newTasks = await getNextTask(
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this.taskCreationChain,
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result,
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task.task_name,
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this.taskList.map((t) => t.task_name),
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objective
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)
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newTasks.forEach((newTask) => {
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this.taskIdCounter += 1
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// eslint-disable-next-line no-param-reassign
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newTask.task_id = this.taskIdCounter
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this.addTask(newTask)
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})
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this.taskList = await prioritizeTasks(this.taskPrioritizationChain, thisTaskId, this.taskList, objective)
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}
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numIters += 1
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if (this.maxIterations !== null && numIters === this.maxIterations) {
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// eslint-disable-next-line no-console
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console.log('\x1b[91m\x1b[1m\n*****TASK ENDING*****\n\x1b[0m\x1b[0m')
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loop = false
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this.taskList = []
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}
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}
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return finalResult
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}
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static fromLLM(llm: BaseChatModel, vectorstore: VectorStore, maxIterations = 3): BabyAGI {
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const taskCreationChain = TaskCreationChain.from_llm(llm)
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const taskPrioritizationChain = TaskPrioritizationChain.from_llm(llm)
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const executionChain = ExecutionChain.from_llm(llm)
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return new BabyAGI(taskCreationChain, taskPrioritizationChain, executionChain, vectorstore, maxIterations)
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}
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}
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@@ -0,0 +1,311 @@
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{
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"description": "Use BabyAGI to create tasks and reprioritize for a given objective",
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"nodes": [
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{
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"width": 300,
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"height": 472,
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"id": "chatOpenAI_0",
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"position": {
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"x": 623.4625717728469,
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"y": -384.9179263816219
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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"],
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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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||||||
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"label": "OpenAI Api Key",
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"name": "openAIApiKey",
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"type": "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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||||||
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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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||||||
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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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||||||
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"label": "gpt-3.5-turbo-0301",
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||||||
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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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||||||
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"optional": true
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||||||
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},
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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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}
|
||||||
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],
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||||||
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"inputAnchors": [],
|
||||||
|
"inputs": {
|
||||||
|
"modelName": "gpt-3.5-turbo",
|
||||||
|
"temperature": "0"
|
||||||
|
},
|
||||||
|
"outputAnchors": [
|
||||||
|
{
|
||||||
|
"id": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel",
|
||||||
|
"name": "chatOpenAI",
|
||||||
|
"label": "ChatOpenAI",
|
||||||
|
"type": "ChatOpenAI | BaseChatModel | BaseLanguageModel"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"selected": false
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||||||
|
},
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||||||
|
"selected": false,
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"positionAbsolute": {
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"x": 623.4625717728469,
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|
"y": -384.9179263816219
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||||||
|
},
|
||||||
|
"dragging": false
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||||||
|
},
|
||||||
|
{
|
||||||
|
"width": 300,
|
||||||
|
"height": 278,
|
||||||
|
"id": "openAIEmbeddings_0",
|
||||||
|
"position": {
|
||||||
|
"x": -85.14926831129219,
|
||||||
|
"y": -175.8984338500009
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|
},
|
||||||
|
"type": "customNode",
|
||||||
|
"data": {
|
||||||
|
"id": "openAIEmbeddings_0",
|
||||||
|
"label": "OpenAI Embeddings",
|
||||||
|
"name": "openAIEmbeddings",
|
||||||
|
"type": "OpenAIEmbeddings",
|
||||||
|
"baseClasses": ["OpenAIEmbeddings", "Embeddings"],
|
||||||
|
"category": "Embeddings",
|
||||||
|
"description": "OpenAI API to generate embeddings for a given text",
|
||||||
|
"inputParams": [
|
||||||
|
{
|
||||||
|
"label": "OpenAI Api Key",
|
||||||
|
"name": "openAIApiKey",
|
||||||
|
"type": "password"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"inputAnchors": [],
|
||||||
|
"inputs": {},
|
||||||
|
"outputAnchors": [
|
||||||
|
{
|
||||||
|
"id": "openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings",
|
||||||
|
"name": "openAIEmbeddings",
|
||||||
|
"label": "OpenAIEmbeddings",
|
||||||
|
"type": "OpenAIEmbeddings | Embeddings"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"selected": false
|
||||||
|
},
|
||||||
|
"selected": false,
|
||||||
|
"positionAbsolute": {
|
||||||
|
"x": -85.14926831129219,
|
||||||
|
"y": -175.8984338500009
|
||||||
|
},
|
||||||
|
"dragging": false
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"width": 300,
|
||||||
|
"height": 552,
|
||||||
|
"id": "pineconeExistingIndex_0",
|
||||||
|
"position": {
|
||||||
|
"x": 264.86118448732543,
|
||||||
|
"y": -305.52350050145094
|
||||||
|
},
|
||||||
|
"type": "customNode",
|
||||||
|
"data": {
|
||||||
|
"id": "pineconeExistingIndex_0",
|
||||||
|
"label": "Pinecone Load Existing Index",
|
||||||
|
"name": "pineconeExistingIndex",
|
||||||
|
"type": "Pinecone",
|
||||||
|
"baseClasses": ["Pinecone", "BaseRetriever"],
|
||||||
|
"category": "Vector Stores",
|
||||||
|
"description": "Load existing index from Pinecone (i.e: Document has been upserted)",
|
||||||
|
"inputParams": [
|
||||||
|
{
|
||||||
|
"label": "Pinecone Api Key",
|
||||||
|
"name": "pineconeApiKey",
|
||||||
|
"type": "password",
|
||||||
|
"id": "pineconeExistingIndex_0-input-pineconeApiKey-password"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"label": "Pinecone Environment",
|
||||||
|
"name": "pineconeEnv",
|
||||||
|
"type": "string",
|
||||||
|
"id": "pineconeExistingIndex_0-input-pineconeEnv-string"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"label": "Pinecone Index",
|
||||||
|
"name": "pineconeIndex",
|
||||||
|
"type": "string",
|
||||||
|
"id": "pineconeExistingIndex_0-input-pineconeIndex-string"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"inputAnchors": [
|
||||||
|
{
|
||||||
|
"label": "Embeddings",
|
||||||
|
"name": "embeddings",
|
||||||
|
"type": "Embeddings",
|
||||||
|
"id": "pineconeExistingIndex_0-input-embeddings-Embeddings"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"inputs": {
|
||||||
|
"embeddings": "{{openAIEmbeddings_0.data.instance}}",
|
||||||
|
"pineconeEnv": "us-west4-gcp",
|
||||||
|
"pineconeIndex": "test"
|
||||||
|
},
|
||||||
|
"outputAnchors": [
|
||||||
|
{
|
||||||
|
"name": "output",
|
||||||
|
"label": "Output",
|
||||||
|
"type": "options",
|
||||||
|
"options": [
|
||||||
|
{
|
||||||
|
"id": "pineconeExistingIndex_0-output-retriever-Pinecone|BaseRetriever",
|
||||||
|
"name": "retriever",
|
||||||
|
"label": "Pinecone Retriever",
|
||||||
|
"type": "Pinecone | BaseRetriever"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"id": "pineconeExistingIndex_0-output-vectorStore-Pinecone|VectorStore",
|
||||||
|
"name": "vectorStore",
|
||||||
|
"label": "Pinecone Vector Store",
|
||||||
|
"type": "Pinecone | VectorStore"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"default": "retriever"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"outputs": {
|
||||||
|
"output": "vectorStore"
|
||||||
|
},
|
||||||
|
"selected": false
|
||||||
|
},
|
||||||
|
"selected": false,
|
||||||
|
"positionAbsolute": {
|
||||||
|
"x": 264.86118448732543,
|
||||||
|
"y": -305.52350050145094
|
||||||
|
},
|
||||||
|
"dragging": false
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"width": 300,
|
||||||
|
"height": 379,
|
||||||
|
"id": "babyAGI_0",
|
||||||
|
"position": {
|
||||||
|
"x": 982.9913269506158,
|
||||||
|
"y": -53.95939754784533
|
||||||
|
},
|
||||||
|
"type": "customNode",
|
||||||
|
"data": {
|
||||||
|
"id": "babyAGI_0",
|
||||||
|
"label": "BabyAGI",
|
||||||
|
"name": "babyAGI",
|
||||||
|
"type": "BabyAGI",
|
||||||
|
"baseClasses": ["BabyAGI"],
|
||||||
|
"category": "Agents",
|
||||||
|
"description": "Task Driven Autonomous Agent which creates new task and reprioritizes task list based on objective",
|
||||||
|
"inputParams": [
|
||||||
|
{
|
||||||
|
"label": "Task Loop",
|
||||||
|
"name": "taskLoop",
|
||||||
|
"type": "number",
|
||||||
|
"default": 3,
|
||||||
|
"id": "babyAGI_0-input-taskLoop-number"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"inputAnchors": [
|
||||||
|
{
|
||||||
|
"label": "Chat Model",
|
||||||
|
"name": "model",
|
||||||
|
"type": "BaseChatModel",
|
||||||
|
"id": "babyAGI_0-input-model-BaseChatModel"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"label": "Vector Store",
|
||||||
|
"name": "vectorStore",
|
||||||
|
"type": "VectorStore",
|
||||||
|
"id": "babyAGI_0-input-vectorStore-VectorStore"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"inputs": {
|
||||||
|
"model": "{{chatOpenAI_0.data.instance}}",
|
||||||
|
"vectorStore": "{{pineconeExistingIndex_0.data.instance}}",
|
||||||
|
"taskLoop": 3
|
||||||
|
},
|
||||||
|
"outputAnchors": [
|
||||||
|
{
|
||||||
|
"id": "babyAGI_0-output-babyAGI-BabyAGI",
|
||||||
|
"name": "babyAGI",
|
||||||
|
"label": "BabyAGI",
|
||||||
|
"type": "BabyAGI"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"outputs": {},
|
||||||
|
"selected": false
|
||||||
|
},
|
||||||
|
"positionAbsolute": {
|
||||||
|
"x": 982.9913269506158,
|
||||||
|
"y": -53.95939754784533
|
||||||
|
},
|
||||||
|
"selected": false
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"edges": [
|
||||||
|
{
|
||||||
|
"source": "openAIEmbeddings_0",
|
||||||
|
"sourceHandle": "openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings",
|
||||||
|
"target": "pineconeExistingIndex_0",
|
||||||
|
"targetHandle": "pineconeExistingIndex_0-input-embeddings-Embeddings",
|
||||||
|
"type": "buttonedge",
|
||||||
|
"id": "openAIEmbeddings_0-openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings-pineconeExistingIndex_0-pineconeExistingIndex_0-input-embeddings-Embeddings",
|
||||||
|
"data": {
|
||||||
|
"label": ""
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"source": "chatOpenAI_0",
|
||||||
|
"sourceHandle": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel",
|
||||||
|
"target": "babyAGI_0",
|
||||||
|
"targetHandle": "babyAGI_0-input-model-BaseChatModel",
|
||||||
|
"type": "buttonedge",
|
||||||
|
"id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel-babyAGI_0-babyAGI_0-input-model-BaseChatModel",
|
||||||
|
"data": {
|
||||||
|
"label": ""
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"source": "pineconeExistingIndex_0",
|
||||||
|
"sourceHandle": "pineconeExistingIndex_0-output-vectorStore-Pinecone|VectorStore",
|
||||||
|
"target": "babyAGI_0",
|
||||||
|
"targetHandle": "babyAGI_0-input-vectorStore-VectorStore",
|
||||||
|
"type": "buttonedge",
|
||||||
|
"id": "pineconeExistingIndex_0-pineconeExistingIndex_0-output-vectorStore-Pinecone|VectorStore-babyAGI_0-babyAGI_0-input-vectorStore-VectorStore",
|
||||||
|
"data": {
|
||||||
|
"label": ""
|
||||||
|
}
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
@@ -230,77 +230,6 @@
|
|||||||
},
|
},
|
||||||
"dragging": false
|
"dragging": false
|
||||||
},
|
},
|
||||||
{
|
|
||||||
"width": 300,
|
|
||||||
"height": 577,
|
|
||||||
"id": "pineconeUpsert_0",
|
|
||||||
"position": {
|
|
||||||
"x": 1212.220130988712,
|
|
||||||
"y": 526.8130243230098
|
|
||||||
},
|
|
||||||
"type": "customNode",
|
|
||||||
"data": {
|
|
||||||
"id": "pineconeUpsert_0",
|
|
||||||
"label": "Pinecone Upsert Document",
|
|
||||||
"name": "pineconeUpsert",
|
|
||||||
"type": "Pinecone",
|
|
||||||
"baseClasses": ["BaseRetriever"],
|
|
||||||
"category": "Vector Stores",
|
|
||||||
"description": "Upsert documents to Pinecone",
|
|
||||||
"inputParams": [
|
|
||||||
{
|
|
||||||
"label": "Pinecone Api Key",
|
|
||||||
"name": "pineconeApiKey",
|
|
||||||
"type": "password"
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"label": "Pinecone Environment",
|
|
||||||
"name": "pineconeEnv",
|
|
||||||
"type": "string"
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"label": "Pinecone Index",
|
|
||||||
"name": "pineconeIndex",
|
|
||||||
"type": "string"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"inputAnchors": [
|
|
||||||
{
|
|
||||||
"label": "Document",
|
|
||||||
"name": "document",
|
|
||||||
"type": "Document",
|
|
||||||
"id": "pineconeUpsert_0-input-document-Document"
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"label": "Embeddings",
|
|
||||||
"name": "embeddings",
|
|
||||||
"type": "Embeddings",
|
|
||||||
"id": "pineconeUpsert_0-input-embeddings-Embeddings"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"inputs": {
|
|
||||||
"document": "{{textFile_0.data.instance}}",
|
|
||||||
"embeddings": "{{openAIEmbeddings_0.data.instance}}",
|
|
||||||
"pineconeEnv": "us-west4-gcp",
|
|
||||||
"pineconeIndex": "test"
|
|
||||||
},
|
|
||||||
"outputAnchors": [
|
|
||||||
{
|
|
||||||
"id": "pineconeUpsert_0-output-pineconeUpsert-BaseRetriever",
|
|
||||||
"name": "pineconeUpsert",
|
|
||||||
"label": "Pinecone",
|
|
||||||
"type": "BaseRetriever"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"selected": false
|
|
||||||
},
|
|
||||||
"selected": false,
|
|
||||||
"positionAbsolute": {
|
|
||||||
"x": 1212.220130988712,
|
|
||||||
"y": 526.8130243230098
|
|
||||||
},
|
|
||||||
"dragging": false
|
|
||||||
},
|
|
||||||
{
|
{
|
||||||
"width": 300,
|
"width": 300,
|
||||||
"height": 280,
|
"height": 280,
|
||||||
@@ -353,6 +282,97 @@
|
|||||||
"y": 410.3973881655837
|
"y": 410.3973881655837
|
||||||
},
|
},
|
||||||
"dragging": false
|
"dragging": false
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"width": 300,
|
||||||
|
"height": 603,
|
||||||
|
"id": "pineconeUpsert_0",
|
||||||
|
"position": {
|
||||||
|
"x": 1207.9646568749058,
|
||||||
|
"y": 531.8684248168081
|
||||||
|
},
|
||||||
|
"type": "customNode",
|
||||||
|
"data": {
|
||||||
|
"id": "pineconeUpsert_0",
|
||||||
|
"label": "Pinecone Upsert Document",
|
||||||
|
"name": "pineconeUpsert",
|
||||||
|
"type": "Pinecone",
|
||||||
|
"baseClasses": ["Pinecone", "BaseRetriever"],
|
||||||
|
"category": "Vector Stores",
|
||||||
|
"description": "Upsert documents to Pinecone",
|
||||||
|
"inputParams": [
|
||||||
|
{
|
||||||
|
"label": "Pinecone Api Key",
|
||||||
|
"name": "pineconeApiKey",
|
||||||
|
"type": "password",
|
||||||
|
"id": "pineconeUpsert_0-input-pineconeApiKey-password"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"label": "Pinecone Environment",
|
||||||
|
"name": "pineconeEnv",
|
||||||
|
"type": "string",
|
||||||
|
"id": "pineconeUpsert_0-input-pineconeEnv-string"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"label": "Pinecone Index",
|
||||||
|
"name": "pineconeIndex",
|
||||||
|
"type": "string",
|
||||||
|
"id": "pineconeUpsert_0-input-pineconeIndex-string"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"inputAnchors": [
|
||||||
|
{
|
||||||
|
"label": "Document",
|
||||||
|
"name": "document",
|
||||||
|
"type": "Document",
|
||||||
|
"id": "pineconeUpsert_0-input-document-Document"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"label": "Embeddings",
|
||||||
|
"name": "embeddings",
|
||||||
|
"type": "Embeddings",
|
||||||
|
"id": "pineconeUpsert_0-input-embeddings-Embeddings"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"inputs": {
|
||||||
|
"document": "{{textFile_0.data.instance}}",
|
||||||
|
"embeddings": "{{openAIEmbeddings_0.data.instance}}",
|
||||||
|
"pineconeEnv": "us-west4-gcp",
|
||||||
|
"pineconeIndex": "test"
|
||||||
|
},
|
||||||
|
"outputAnchors": [
|
||||||
|
{
|
||||||
|
"name": "output",
|
||||||
|
"label": "Output",
|
||||||
|
"type": "options",
|
||||||
|
"options": [
|
||||||
|
{
|
||||||
|
"id": "pineconeUpsert_0-output-retriever-Pinecone|BaseRetriever",
|
||||||
|
"name": "retriever",
|
||||||
|
"label": "Pinecone Retriever",
|
||||||
|
"type": "Pinecone | BaseRetriever"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"id": "pineconeUpsert_0-output-vectorStore-Pinecone|VectorStore",
|
||||||
|
"name": "vectorStore",
|
||||||
|
"label": "Pinecone Vector Store",
|
||||||
|
"type": "Pinecone | VectorStore"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"default": "retriever"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"outputs": {
|
||||||
|
"output": "retriever"
|
||||||
|
},
|
||||||
|
"selected": false
|
||||||
|
},
|
||||||
|
"selected": false,
|
||||||
|
"positionAbsolute": {
|
||||||
|
"x": 1207.9646568749058,
|
||||||
|
"y": 531.8684248168081
|
||||||
|
},
|
||||||
|
"dragging": false
|
||||||
}
|
}
|
||||||
],
|
],
|
||||||
"edges": [
|
"edges": [
|
||||||
@@ -367,6 +387,28 @@
|
|||||||
"label": ""
|
"label": ""
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
|
{
|
||||||
|
"source": "openAI_0",
|
||||||
|
"sourceHandle": "openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel",
|
||||||
|
"target": "conversationalRetrievalQAChain_0",
|
||||||
|
"targetHandle": "conversationalRetrievalQAChain_0-input-llm-BaseLLM",
|
||||||
|
"type": "buttonedge",
|
||||||
|
"id": "openAI_0-openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-llm-BaseLLM",
|
||||||
|
"data": {
|
||||||
|
"label": ""
|
||||||
|
}
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"source": "pineconeUpsert_0",
|
||||||
|
"sourceHandle": "pineconeUpsert_0-output-retriever-Pinecone|BaseRetriever",
|
||||||
|
"target": "conversationalRetrievalQAChain_0",
|
||||||
|
"targetHandle": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
|
||||||
|
"type": "buttonedge",
|
||||||
|
"id": "pineconeUpsert_0-pineconeUpsert_0-output-retriever-Pinecone|BaseRetriever-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
|
||||||
|
"data": {
|
||||||
|
"label": ""
|
||||||
|
}
|
||||||
|
},
|
||||||
{
|
{
|
||||||
"source": "textFile_0",
|
"source": "textFile_0",
|
||||||
"sourceHandle": "textFile_0-output-textFile-Document",
|
"sourceHandle": "textFile_0-output-textFile-Document",
|
||||||
@@ -388,28 +430,6 @@
|
|||||||
"data": {
|
"data": {
|
||||||
"label": ""
|
"label": ""
|
||||||
}
|
}
|
||||||
},
|
|
||||||
{
|
|
||||||
"source": "openAI_0",
|
|
||||||
"sourceHandle": "openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel",
|
|
||||||
"target": "conversationalRetrievalQAChain_0",
|
|
||||||
"targetHandle": "conversationalRetrievalQAChain_0-input-llm-BaseLLM",
|
|
||||||
"type": "buttonedge",
|
|
||||||
"id": "openAI_0-openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-llm-BaseLLM",
|
|
||||||
"data": {
|
|
||||||
"label": ""
|
|
||||||
}
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"source": "pineconeUpsert_0",
|
|
||||||
"sourceHandle": "pineconeUpsert_0-output-pineconeUpsert-BaseRetriever",
|
|
||||||
"target": "conversationalRetrievalQAChain_0",
|
|
||||||
"targetHandle": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
|
|
||||||
"type": "buttonedge",
|
|
||||||
"id": "pineconeUpsert_0-pineconeUpsert_0-output-pineconeUpsert-BaseRetriever-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
|
|
||||||
"data": {
|
|
||||||
"label": ""
|
|
||||||
}
|
|
||||||
}
|
}
|
||||||
]
|
]
|
||||||
}
|
}
|
||||||
|
|||||||
@@ -245,77 +245,6 @@
|
|||||||
},
|
},
|
||||||
"dragging": false
|
"dragging": false
|
||||||
},
|
},
|
||||||
{
|
|
||||||
"width": 300,
|
|
||||||
"height": 577,
|
|
||||||
"id": "pineconeUpsert_0",
|
|
||||||
"position": {
|
|
||||||
"x": 1265.1304547629002,
|
|
||||||
"y": 376.13121569675315
|
|
||||||
},
|
|
||||||
"type": "customNode",
|
|
||||||
"data": {
|
|
||||||
"id": "pineconeUpsert_0",
|
|
||||||
"label": "Pinecone Upsert Document",
|
|
||||||
"name": "pineconeUpsert",
|
|
||||||
"type": "Pinecone",
|
|
||||||
"baseClasses": ["BaseRetriever"],
|
|
||||||
"category": "Vector Stores",
|
|
||||||
"description": "Upsert documents to Pinecone",
|
|
||||||
"inputParams": [
|
|
||||||
{
|
|
||||||
"label": "Pinecone Api Key",
|
|
||||||
"name": "pineconeApiKey",
|
|
||||||
"type": "password"
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"label": "Pinecone Environment",
|
|
||||||
"name": "pineconeEnv",
|
|
||||||
"type": "string"
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"label": "Pinecone Index",
|
|
||||||
"name": "pineconeIndex",
|
|
||||||
"type": "string"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"inputAnchors": [
|
|
||||||
{
|
|
||||||
"label": "Document",
|
|
||||||
"name": "document",
|
|
||||||
"type": "Document",
|
|
||||||
"id": "pineconeUpsert_0-input-document-Document"
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"label": "Embeddings",
|
|
||||||
"name": "embeddings",
|
|
||||||
"type": "Embeddings",
|
|
||||||
"id": "pineconeUpsert_0-input-embeddings-Embeddings"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"inputs": {
|
|
||||||
"document": "{{github_0.data.instance}}",
|
|
||||||
"embeddings": "{{openAIEmbeddings_0.data.instance}}",
|
|
||||||
"pineconeEnv": "us-west4-gcp",
|
|
||||||
"pineconeIndex": "test"
|
|
||||||
},
|
|
||||||
"outputAnchors": [
|
|
||||||
{
|
|
||||||
"id": "pineconeUpsert_0-output-pineconeUpsert-BaseRetriever",
|
|
||||||
"name": "pineconeUpsert",
|
|
||||||
"label": "Pinecone",
|
|
||||||
"type": "BaseRetriever"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"selected": false
|
|
||||||
},
|
|
||||||
"selected": false,
|
|
||||||
"positionAbsolute": {
|
|
||||||
"x": 1265.1304547629002,
|
|
||||||
"y": 376.13121569675315
|
|
||||||
},
|
|
||||||
"dragging": false
|
|
||||||
},
|
|
||||||
{
|
{
|
||||||
"width": 300,
|
"width": 300,
|
||||||
"height": 280,
|
"height": 280,
|
||||||
@@ -368,6 +297,97 @@
|
|||||||
"y": 197.0636463189023
|
"y": 197.0636463189023
|
||||||
},
|
},
|
||||||
"dragging": false
|
"dragging": false
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"width": 300,
|
||||||
|
"height": 603,
|
||||||
|
"id": "pineconeUpsert_0",
|
||||||
|
"position": {
|
||||||
|
"x": 1275.7940479898277,
|
||||||
|
"y": 379.2784546164221
|
||||||
|
},
|
||||||
|
"type": "customNode",
|
||||||
|
"data": {
|
||||||
|
"id": "pineconeUpsert_0",
|
||||||
|
"label": "Pinecone Upsert Document",
|
||||||
|
"name": "pineconeUpsert",
|
||||||
|
"type": "Pinecone",
|
||||||
|
"baseClasses": ["Pinecone", "BaseRetriever"],
|
||||||
|
"category": "Vector Stores",
|
||||||
|
"description": "Upsert documents to Pinecone",
|
||||||
|
"inputParams": [
|
||||||
|
{
|
||||||
|
"label": "Pinecone Api Key",
|
||||||
|
"name": "pineconeApiKey",
|
||||||
|
"type": "password",
|
||||||
|
"id": "pineconeUpsert_0-input-pineconeApiKey-password"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"label": "Pinecone Environment",
|
||||||
|
"name": "pineconeEnv",
|
||||||
|
"type": "string",
|
||||||
|
"id": "pineconeUpsert_0-input-pineconeEnv-string"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"label": "Pinecone Index",
|
||||||
|
"name": "pineconeIndex",
|
||||||
|
"type": "string",
|
||||||
|
"id": "pineconeUpsert_0-input-pineconeIndex-string"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"inputAnchors": [
|
||||||
|
{
|
||||||
|
"label": "Document",
|
||||||
|
"name": "document",
|
||||||
|
"type": "Document",
|
||||||
|
"id": "pineconeUpsert_0-input-document-Document"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"label": "Embeddings",
|
||||||
|
"name": "embeddings",
|
||||||
|
"type": "Embeddings",
|
||||||
|
"id": "pineconeUpsert_0-input-embeddings-Embeddings"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"inputs": {
|
||||||
|
"document": "{{github_0.data.instance}}",
|
||||||
|
"embeddings": "{{openAIEmbeddings_0.data.instance}}",
|
||||||
|
"pineconeEnv": "us-west4-gcp",
|
||||||
|
"pineconeIndex": "test"
|
||||||
|
},
|
||||||
|
"outputAnchors": [
|
||||||
|
{
|
||||||
|
"name": "output",
|
||||||
|
"label": "Output",
|
||||||
|
"type": "options",
|
||||||
|
"options": [
|
||||||
|
{
|
||||||
|
"id": "pineconeUpsert_0-output-retriever-Pinecone|BaseRetriever",
|
||||||
|
"name": "retriever",
|
||||||
|
"label": "Pinecone Retriever",
|
||||||
|
"type": "Pinecone | BaseRetriever"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"id": "pineconeUpsert_0-output-vectorStore-Pinecone|VectorStore",
|
||||||
|
"name": "vectorStore",
|
||||||
|
"label": "Pinecone Vector Store",
|
||||||
|
"type": "Pinecone | VectorStore"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"default": "retriever"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"outputs": {
|
||||||
|
"output": "retriever"
|
||||||
|
},
|
||||||
|
"selected": false
|
||||||
|
},
|
||||||
|
"selected": false,
|
||||||
|
"positionAbsolute": {
|
||||||
|
"x": 1275.7940479898277,
|
||||||
|
"y": 379.2784546164221
|
||||||
|
},
|
||||||
|
"dragging": false
|
||||||
}
|
}
|
||||||
],
|
],
|
||||||
"edges": [
|
"edges": [
|
||||||
@@ -383,12 +403,12 @@
|
|||||||
}
|
}
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"source": "pineconeUpsert_0",
|
"source": "recursiveCharacterTextSplitter_0",
|
||||||
"sourceHandle": "pineconeUpsert_0-output-pineconeUpsert-BaseRetriever",
|
"sourceHandle": "recursiveCharacterTextSplitter_0-output-recursiveCharacterTextSplitter-RecursiveCharacterTextSplitter|TextSplitter",
|
||||||
"target": "conversationalRetrievalQAChain_0",
|
"target": "github_0",
|
||||||
"targetHandle": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
|
"targetHandle": "github_0-input-textSplitter-TextSplitter",
|
||||||
"type": "buttonedge",
|
"type": "buttonedge",
|
||||||
"id": "pineconeUpsert_0-pineconeUpsert_0-output-pineconeUpsert-BaseRetriever-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
|
"id": "recursiveCharacterTextSplitter_0-recursiveCharacterTextSplitter_0-output-recursiveCharacterTextSplitter-RecursiveCharacterTextSplitter|TextSplitter-github_0-github_0-input-textSplitter-TextSplitter",
|
||||||
"data": {
|
"data": {
|
||||||
"label": ""
|
"label": ""
|
||||||
}
|
}
|
||||||
@@ -416,12 +436,12 @@
|
|||||||
}
|
}
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"source": "recursiveCharacterTextSplitter_0",
|
"source": "pineconeUpsert_0",
|
||||||
"sourceHandle": "recursiveCharacterTextSplitter_0-output-recursiveCharacterTextSplitter-RecursiveCharacterTextSplitter|TextSplitter",
|
"sourceHandle": "pineconeUpsert_0-output-retriever-Pinecone|BaseRetriever",
|
||||||
"target": "github_0",
|
"target": "conversationalRetrievalQAChain_0",
|
||||||
"targetHandle": "github_0-input-textSplitter-TextSplitter",
|
"targetHandle": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
|
||||||
"type": "buttonedge",
|
"type": "buttonedge",
|
||||||
"id": "recursiveCharacterTextSplitter_0-recursiveCharacterTextSplitter_0-output-recursiveCharacterTextSplitter-RecursiveCharacterTextSplitter|TextSplitter-github_0-github_0-input-textSplitter-TextSplitter",
|
"id": "pineconeUpsert_0-pineconeUpsert_0-output-retriever-Pinecone|BaseRetriever-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
|
||||||
"data": {
|
"data": {
|
||||||
"label": ""
|
"label": ""
|
||||||
}
|
}
|
||||||
|
|||||||
Reference in New Issue
Block a user