mirror of https://github.com/FlowiseAI/Flowise.git
Merge pull request #171 from FlowiseAI/feature/MultiPromptChain
Feature/MultiPromptChainpull/179/head
Henry Heng
GitHub
commit
2802ee0142
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@ -56,7 +56,8 @@ class ConversationChain_Chains implements INode {
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const obj: any = {
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llm: model,
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memory
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memory,
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verbose: process.env.DEBUG === 'true' ? true : false
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}
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const chatPrompt = ChatPromptTemplate.fromPromptMessages([
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@ -0,0 +1,68 @@
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import { BaseLanguageModel } from 'langchain/base_language'
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import { INode, INodeData, INodeParams, PromptRetriever } from '../../../src/Interface'
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import { getBaseClasses } from '../../../src/utils'
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import { MultiPromptChain } from 'langchain/chains'
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class MultiPromptChain_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 = 'Multi Prompt Chain'
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this.name = 'multiPromptChain'
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this.type = 'MultiPromptChain'
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this.icon = 'chain.svg'
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this.category = 'Chains'
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this.description = 'Chain automatically picks an appropriate prompt from multiple prompt templates'
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this.baseClasses = [this.type, ...getBaseClasses(MultiPromptChain)]
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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: 'BaseLanguageModel'
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},
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{
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label: 'Prompt Retriever',
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name: 'promptRetriever',
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type: 'PromptRetriever',
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list: true
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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 BaseLanguageModel
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const promptRetriever = nodeData.inputs?.promptRetriever as PromptRetriever[]
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const promptNames = []
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const promptDescriptions = []
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const promptTemplates = []
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for (const prompt of promptRetriever) {
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promptNames.push(prompt.name)
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promptDescriptions.push(prompt.description)
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promptTemplates.push(prompt.systemMessage)
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}
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const chain = MultiPromptChain.fromPrompts(model, promptNames, promptDescriptions, promptTemplates, undefined, {
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verbose: process.env.DEBUG === 'true' ? true : false
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} as any)
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return chain
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}
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async run(nodeData: INodeData, input: string): Promise<string> {
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const chain = nodeData.instance as MultiPromptChain
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const res = await chain.call({ input })
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return res?.text
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}
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}
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module.exports = { nodeClass: MultiPromptChain_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 +1,62 @@
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import { INode, INodeData, INodeParams, PromptRetriever, PromptRetrieverInput } from '../../../src/Interface'
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class PromptRetriever_Retrievers 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 = 'Prompt Retriever'
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this.name = 'promptRetriever'
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this.type = 'PromptRetriever'
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this.icon = 'promptretriever.svg'
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this.category = 'Retrievers'
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this.description = 'Store prompt template with name & description to be later queried by MultiPromptChain'
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this.baseClasses = [this.type]
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this.inputs = [
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{
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label: 'Prompt Name',
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name: 'name',
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type: 'string',
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placeholder: 'physics-qa'
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},
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{
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label: 'Prompt Description',
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name: 'description',
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type: 'string',
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rows: 3,
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description: 'Description of what the prompt does and when it should be used',
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placeholder: 'Good for answering questions about physics'
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},
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{
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label: 'Prompt System Message',
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name: 'systemMessage',
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type: 'string',
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rows: 4,
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placeholder: `You are a very smart physics professor. You are great at answering questions about physics in a concise and easy to understand manner. When you don't know the answer to a question you admit that you don't know.`
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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 name = nodeData.inputs?.name as string
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const description = nodeData.inputs?.description as string
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const systemMessage = nodeData.inputs?.systemMessage as string
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const obj = {
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name,
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description,
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systemMessage
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} as PromptRetrieverInput
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const retriever = new PromptRetriever(obj)
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return retriever
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}
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}
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module.exports = { nodeClass: PromptRetriever_Retrievers }
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@ -0,0 +1,8 @@
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<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-message-down" 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="M8 9h8"></path>
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<path d="M8 13h6"></path>
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<path d="M11.998 18.601l-3.998 2.399v-3h-2a3 3 0 0 1 -3 -3v-8a3 3 0 0 1 3 -3h12a3 3 0 0 1 3 3v5.5"></path>
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<path d="M19 16v6"></path>
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<path d="M22 19l-3 3l-3 -3"></path>
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</svg>
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After Width: | Height: | Size: 535 B |
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@ -103,3 +103,24 @@ export class PromptTemplate extends LangchainPromptTemplate {
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super(input)
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}
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}
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export interface PromptRetrieverInput {
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name: string
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description: string
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systemMessage: string
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}
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const fixedTemplate = `Here is a question:
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{input}
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`
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export class PromptRetriever {
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name: string
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description: string
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systemMessage: string
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constructor(fields: PromptRetrieverInput) {
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this.name = fields.name
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this.description = fields.description
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this.systemMessage = `${fields.systemMessage}\n${fixedTemplate}`
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}
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}
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@ -0,0 +1,442 @@
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{
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"description": "A chain that automatically picks an appropriate prompt from multiple prompts",
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"nodes": [
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{
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"width": 300,
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"height": 632,
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"id": "promptRetriever_0",
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"position": {
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"x": 197.46642699727397,
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"y": 25.945621297410923
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},
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"type": "customNode",
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"data": {
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"id": "promptRetriever_0",
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"label": "Prompt Retriever",
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"name": "promptRetriever",
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"type": "PromptRetriever",
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"baseClasses": ["PromptRetriever"],
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"category": "Retrievers",
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"description": "Store prompt template with name & description to be later queried by MultiPromptChain",
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"inputParams": [
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{
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"label": "Prompt Name",
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"name": "name",
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"type": "string",
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"placeholder": "physics-qa",
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"id": "promptRetriever_0-input-name-string"
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},
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{
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"label": "Prompt Description",
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"name": "description",
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"type": "string",
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"rows": 3,
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"description": "Description of what the prompt does and when it should be used",
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"placeholder": "Good for answering questions about physics",
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"id": "promptRetriever_0-input-description-string"
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},
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{
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"label": "Prompt System Message",
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"name": "systemMessage",
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"type": "string",
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"rows": 4,
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"placeholder": "You are a very smart physics professor. You are great at answering questions about physics in a concise and easy to understand manner. When you don't know the answer to a question you admit that you don't know.",
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"id": "promptRetriever_0-input-systemMessage-string"
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}
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],
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"inputAnchors": [],
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"inputs": {
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"name": "physics",
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"description": "Good for answering questions about physics",
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"systemMessage": "You are a very smart physics professor. You are great at answering questions about physics in a concise and easy to understand manner. When you don't know the answer to a question you admit that you don't know."
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},
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"outputAnchors": [
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{
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"id": "promptRetriever_0-output-promptRetriever-PromptRetriever",
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"name": "promptRetriever",
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"label": "PromptRetriever",
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"type": "PromptRetriever"
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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": 197.46642699727397,
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"y": 25.945621297410923
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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": 280,
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"id": "multiPromptChain_0",
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"position": {
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"x": 1619.1305522575494,
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"y": 210.28103293821243
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},
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"type": "customNode",
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"data": {
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"id": "multiPromptChain_0",
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"label": "Multi Prompt Chain",
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"name": "multiPromptChain",
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"type": "MultiPromptChain",
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"baseClasses": ["MultiPromptChain", "MultiRouteChain", "BaseChain", "BaseLangChain"],
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"category": "Chains",
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"description": "Chain automatically picks an appropriate prompt from multiple prompt templates",
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"inputParams": [],
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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": "BaseLanguageModel",
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"id": "multiPromptChain_0-input-model-BaseLanguageModel"
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},
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{
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"label": "Prompt Retriever",
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"name": "promptRetriever",
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"type": "PromptRetriever",
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"list": true,
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"id": "multiPromptChain_0-input-promptRetriever-PromptRetriever"
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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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"promptRetriever": [
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"{{promptRetriever_0.data.instance}}",
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"{{promptRetriever_2.data.instance}}",
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"{{promptRetriever_1.data.instance}}"
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]
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},
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"outputAnchors": [
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{
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"id": "multiPromptChain_0-output-multiPromptChain-MultiPromptChain|MultiRouteChain|BaseChain|BaseLangChain",
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"name": "multiPromptChain",
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"label": "MultiPromptChain",
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"type": "MultiPromptChain | MultiRouteChain | 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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"positionAbsolute": {
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"x": 1619.1305522575494,
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"y": 210.28103293821243
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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": 632,
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"id": "promptRetriever_1",
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"position": {
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"x": 539.1322780233141,
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"y": -250.72967142925938
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},
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"type": "customNode",
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"data": {
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"id": "promptRetriever_1",
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"label": "Prompt Retriever",
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"name": "promptRetriever",
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"type": "PromptRetriever",
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"baseClasses": ["PromptRetriever"],
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"category": "Retrievers",
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"description": "Store prompt template with name & description to be later queried by MultiPromptChain",
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"inputParams": [
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{
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"label": "Prompt Name",
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"name": "name",
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"type": "string",
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"placeholder": "physics-qa",
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"id": "promptRetriever_1-input-name-string"
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},
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{
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"label": "Prompt Description",
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"name": "description",
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"type": "string",
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"rows": 3,
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"description": "Description of what the prompt does and when it should be used",
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"placeholder": "Good for answering questions about physics",
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"id": "promptRetriever_1-input-description-string"
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},
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{
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"label": "Prompt System Message",
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"name": "systemMessage",
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"type": "string",
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"rows": 4,
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"placeholder": "You are a very smart physics professor. You are great at answering questions about physics in a concise and easy to understand manner. When you don't know the answer to a question you admit that you don't know.",
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"id": "promptRetriever_1-input-systemMessage-string"
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}
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],
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"inputAnchors": [],
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"inputs": {
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"name": "math",
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"description": "Good for answering math questions",
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"systemMessage": "You are a very good mathematician. You are great at answering math questions. You are so good because you are able to break down hard problems into their component parts, answer the component parts, and then put them together to answer the broader question."
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},
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"outputAnchors": [
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{
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"id": "promptRetriever_1-output-promptRetriever-PromptRetriever",
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"name": "promptRetriever",
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"label": "PromptRetriever",
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"type": "PromptRetriever"
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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": 539.1322780233141,
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"y": -250.72967142925938
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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": 632,
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"id": "promptRetriever_2",
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"position": {
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"x": 872.6184534864304,
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"y": -366.9443140594265
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},
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"type": "customNode",
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"data": {
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"id": "promptRetriever_2",
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"label": "Prompt Retriever",
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"name": "promptRetriever",
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"type": "PromptRetriever",
|
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"baseClasses": ["PromptRetriever"],
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"category": "Retrievers",
|
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"description": "Store prompt template with name & description to be later queried by MultiPromptChain",
|
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"inputParams": [
|
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{
|
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"label": "Prompt Name",
|
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"name": "name",
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"type": "string",
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"placeholder": "physics-qa",
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"id": "promptRetriever_2-input-name-string"
|
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},
|
||||
{
|
||||
"label": "Prompt Description",
|
||||
"name": "description",
|
||||
"type": "string",
|
||||
"rows": 3,
|
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"description": "Description of what the prompt does and when it should be used",
|
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"placeholder": "Good for answering questions about physics",
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"id": "promptRetriever_2-input-description-string"
|
||||
},
|
||||
{
|
||||
"label": "Prompt System Message",
|
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"name": "systemMessage",
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"type": "string",
|
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"rows": 4,
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"placeholder": "You are a very smart physics professor. You are great at answering questions about physics in a concise and easy to understand manner. When you don't know the answer to a question you admit that you don't know.",
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"id": "promptRetriever_2-input-systemMessage-string"
|
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}
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],
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"inputAnchors": [],
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"inputs": {
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"name": "history",
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"description": "Good for answering questions about history",
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"systemMessage": "You are a very smart history professor. You are great at answering questions about history in a concise and easy to understand manner. When you don't know the answer to a question you admit that you don't know."
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},
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"outputAnchors": [
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{
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"id": "promptRetriever_2-output-promptRetriever-PromptRetriever",
|
||||
"name": "promptRetriever",
|
||||
"label": "PromptRetriever",
|
||||
"type": "PromptRetriever"
|
||||
}
|
||||
],
|
||||
"outputs": {},
|
||||
"selected": false
|
||||
},
|
||||
"selected": false,
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||||
"positionAbsolute": {
|
||||
"x": 872.6184534864304,
|
||||
"y": -366.9443140594265
|
||||
},
|
||||
"dragging": false
|
||||
},
|
||||
{
|
||||
"width": 300,
|
||||
"height": 524,
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||||
"id": "chatOpenAI_0",
|
||||
"position": {
|
||||
"x": 1230.07368145571,
|
||||
"y": -296.44522826934826
|
||||
},
|
||||
"type": "customNode",
|
||||
"data": {
|
||||
"id": "chatOpenAI_0",
|
||||
"label": "ChatOpenAI",
|
||||
"name": "chatOpenAI",
|
||||
"type": "ChatOpenAI",
|
||||
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel", "BaseLangChain"],
|
||||
"category": "Chat Models",
|
||||
"description": "Wrapper around OpenAI large language models that use the Chat endpoint",
|
||||
"inputParams": [
|
||||
{
|
||||
"label": "OpenAI Api Key",
|
||||
"name": "openAIApiKey",
|
||||
"type": "password",
|
||||
"id": "chatOpenAI_0-input-openAIApiKey-password"
|
||||
},
|
||||
{
|
||||
"label": "Model Name",
|
||||
"name": "modelName",
|
||||
"type": "options",
|
||||
"options": [
|
||||
{
|
||||
"label": "gpt-4",
|
||||
"name": "gpt-4"
|
||||
},
|
||||
{
|
||||
"label": "gpt-4-0314",
|
||||
"name": "gpt-4-0314"
|
||||
},
|
||||
{
|
||||
"label": "gpt-4-32k-0314",
|
||||
"name": "gpt-4-32k-0314"
|
||||
},
|
||||
{
|
||||
"label": "gpt-3.5-turbo",
|
||||
"name": "gpt-3.5-turbo"
|
||||
},
|
||||
{
|
||||
"label": "gpt-3.5-turbo-0301",
|
||||
"name": "gpt-3.5-turbo-0301"
|
||||
}
|
||||
],
|
||||
"default": "gpt-3.5-turbo",
|
||||
"optional": true,
|
||||
"id": "chatOpenAI_0-input-modelName-options"
|
||||
},
|
||||
{
|
||||
"label": "Temperature",
|
||||
"name": "temperature",
|
||||
"type": "number",
|
||||
"default": 0.9,
|
||||
"optional": true,
|
||||
"id": "chatOpenAI_0-input-temperature-number"
|
||||
},
|
||||
{
|
||||
"label": "Max Tokens",
|
||||
"name": "maxTokens",
|
||||
"type": "number",
|
||||
"optional": true,
|
||||
"additionalParams": true,
|
||||
"id": "chatOpenAI_0-input-maxTokens-number"
|
||||
},
|
||||
{
|
||||
"label": "Top Probability",
|
||||
"name": "topP",
|
||||
"type": "number",
|
||||
"optional": true,
|
||||
"additionalParams": true,
|
||||
"id": "chatOpenAI_0-input-topP-number"
|
||||
},
|
||||
{
|
||||
"label": "Frequency Penalty",
|
||||
"name": "frequencyPenalty",
|
||||
"type": "number",
|
||||
"optional": true,
|
||||
"additionalParams": true,
|
||||
"id": "chatOpenAI_0-input-frequencyPenalty-number"
|
||||
},
|
||||
{
|
||||
"label": "Presence Penalty",
|
||||
"name": "presencePenalty",
|
||||
"type": "number",
|
||||
"optional": true,
|
||||
"additionalParams": true,
|
||||
"id": "chatOpenAI_0-input-presencePenalty-number"
|
||||
},
|
||||
{
|
||||
"label": "Timeout",
|
||||
"name": "timeout",
|
||||
"type": "number",
|
||||
"optional": true,
|
||||
"additionalParams": true,
|
||||
"id": "chatOpenAI_0-input-timeout-number"
|
||||
}
|
||||
],
|
||||
"inputAnchors": [],
|
||||
"inputs": {
|
||||
"modelName": "gpt-3.5-turbo",
|
||||
"temperature": 0.9,
|
||||
"maxTokens": "",
|
||||
"topP": "",
|
||||
"frequencyPenalty": "",
|
||||
"presencePenalty": "",
|
||||
"timeout": ""
|
||||
},
|
||||
"outputAnchors": [
|
||||
{
|
||||
"id": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|BaseLangChain",
|
||||
"name": "chatOpenAI",
|
||||
"label": "ChatOpenAI",
|
||||
"type": "ChatOpenAI | BaseChatModel | BaseLanguageModel | BaseLangChain"
|
||||
}
|
||||
],
|
||||
"outputs": {},
|
||||
"selected": false
|
||||
},
|
||||
"selected": false,
|
||||
"positionAbsolute": {
|
||||
"x": 1230.07368145571,
|
||||
"y": -296.44522826934826
|
||||
},
|
||||
"dragging": false
|
||||
}
|
||||
],
|
||||
"edges": [
|
||||
{
|
||||
"source": "promptRetriever_0",
|
||||
"sourceHandle": "promptRetriever_0-output-promptRetriever-PromptRetriever",
|
||||
"target": "multiPromptChain_0",
|
||||
"targetHandle": "multiPromptChain_0-input-promptRetriever-PromptRetriever",
|
||||
"type": "buttonedge",
|
||||
"id": "promptRetriever_0-promptRetriever_0-output-promptRetriever-PromptRetriever-multiPromptChain_0-multiPromptChain_0-input-promptRetriever-PromptRetriever",
|
||||
"data": {
|
||||
"label": ""
|
||||
}
|
||||
},
|
||||
{
|
||||
"source": "promptRetriever_2",
|
||||
"sourceHandle": "promptRetriever_2-output-promptRetriever-PromptRetriever",
|
||||
"target": "multiPromptChain_0",
|
||||
"targetHandle": "multiPromptChain_0-input-promptRetriever-PromptRetriever",
|
||||
"type": "buttonedge",
|
||||
"id": "promptRetriever_2-promptRetriever_2-output-promptRetriever-PromptRetriever-multiPromptChain_0-multiPromptChain_0-input-promptRetriever-PromptRetriever",
|
||||
"data": {
|
||||
"label": ""
|
||||
}
|
||||
},
|
||||
{
|
||||
"source": "promptRetriever_1",
|
||||
"sourceHandle": "promptRetriever_1-output-promptRetriever-PromptRetriever",
|
||||
"target": "multiPromptChain_0",
|
||||
"targetHandle": "multiPromptChain_0-input-promptRetriever-PromptRetriever",
|
||||
"type": "buttonedge",
|
||||
"id": "promptRetriever_1-promptRetriever_1-output-promptRetriever-PromptRetriever-multiPromptChain_0-multiPromptChain_0-input-promptRetriever-PromptRetriever",
|
||||
"data": {
|
||||
"label": ""
|
||||
}
|
||||
},
|
||||
{
|
||||
"source": "chatOpenAI_0",
|
||||
"sourceHandle": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|BaseLangChain",
|
||||
"target": "multiPromptChain_0",
|
||||
"targetHandle": "multiPromptChain_0-input-model-BaseLanguageModel",
|
||||
"type": "buttonedge",
|
||||
"id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|BaseLangChain-multiPromptChain_0-multiPromptChain_0-input-model-BaseLanguageModel",
|
||||
"data": {
|
||||
"label": ""
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
Loading…
Reference in New Issue