Revert the changes to the original parser & template
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parent
95b251f02a
commit
62f70ab6ef
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@ -1,9 +1,8 @@
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import { getBaseClasses, INode, INodeData, INodeParams } from '../../../src'
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import { convertSchemaToZod, getBaseClasses, INode, INodeData, INodeParams } from '../../../src'
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import { BaseOutputParser } from 'langchain/schema/output_parser'
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import { StructuredOutputParser as LangchainStructuredOutputParser } from 'langchain/output_parsers'
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import { CATEGORY } from '../OutputParserHelpers'
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import { z } from 'zod'
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import { jsonToZod } from 'json-to-zod'
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class StructuredOutputParser implements INode {
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label: string
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@ -35,31 +34,44 @@ class StructuredOutputParser implements INode {
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description: 'In the event that the first call fails, will make another call to the model to fix any errors.'
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},
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{
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label: 'Example JSON',
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name: 'exampleJson',
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type: 'string',
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description: 'Example JSON structure for LLM to return',
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rows: 10,
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default: '{"answer": "the answer", "followupQuestions": ["question1", "question2"]}',
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label: 'JSON Structure',
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name: 'jsonStructure',
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type: 'datagrid',
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description: 'JSON structure for LLM to return',
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datagrid: [
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{ field: 'property', headerName: 'Property', editable: true },
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{
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field: 'type',
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headerName: 'Type',
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type: 'singleSelect',
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valueOptions: ['string', 'number', 'boolean'],
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editable: true
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},
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{ field: 'description', headerName: 'Description', editable: true, flex: 1 }
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],
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default: [
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{
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property: 'answer',
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type: 'string',
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description: `answer to the user's question`
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},
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{
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property: 'source',
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type: 'string',
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description: `sources used to answer the question, should be websites`
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}
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],
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additionalParams: 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 exampleJson = nodeData.inputs?.exampleJson as string
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const jsonStructure = nodeData.inputs?.jsonStructure as string
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const autoFix = nodeData.inputs?.autofixParser as boolean
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const jsonToZodString = jsonToZod(JSON.parse(exampleJson))
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const splitString = jsonToZodString.split('const schema = ')
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const schemaString = splitString[1].trim()
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const fnString = `function proxyFn(z){ return ${schemaString} }`
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const zodSchemaFunction = new Function('z', `return ${schemaString}`)
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const zodSchema = zodSchemaFunction(z)
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try {
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const structuredOutputParser = LangchainStructuredOutputParser.fromZodSchema(zodSchema)
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const structuredOutputParser = LangchainStructuredOutputParser.fromZodSchema(z.object(convertSchemaToZod(jsonStructure)))
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// NOTE: When we change Flowise to return a json response, the following has to be changed to: JsonStructuredOutputParser
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Object.defineProperty(structuredOutputParser, 'autoFix', {
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@ -4,7 +4,7 @@
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"nodes": [
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{
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"width": 300,
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"height": 576,
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"height": 574,
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"id": "chatOpenAI_0",
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"position": {
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"x": 845.3961479115309,
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@ -17,12 +17,7 @@
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"version": 3,
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"name": "chatOpenAI",
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"type": "ChatOpenAI",
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"baseClasses": [
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"ChatOpenAI",
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"BaseChatModel",
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"BaseLanguageModel",
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"Runnable"
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],
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"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel", "Runnable"],
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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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@ -30,9 +25,7 @@
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"label": "Connect Credential",
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"name": "credential",
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"type": "credential",
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"credentialNames": [
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"openAIApi"
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],
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"credentialNames": ["openAIApi"],
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"id": "chatOpenAI_0-input-credential-credential"
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},
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{
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@ -209,7 +202,7 @@
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},
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{
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"width": 300,
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"height": 508,
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"height": 456,
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"id": "llmChain_0",
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"position": {
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"x": 1229.1699649849293,
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@ -222,11 +215,7 @@
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"version": 3,
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"name": "llmChain",
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"type": "LLMChain",
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"baseClasses": [
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"LLMChain",
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"BaseChain",
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"Runnable"
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],
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"baseClasses": ["LLMChain", "BaseChain", "Runnable"],
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"category": "Chains",
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"description": "Chain to run queries against LLMs",
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"inputParams": [
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@ -311,7 +300,7 @@
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},
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{
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"width": 300,
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"height": 690,
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"height": 652,
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"id": "chatPromptTemplate_0",
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"position": {
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"x": 501.1597501123828,
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@ -324,12 +313,7 @@
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"version": 1,
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"name": "chatPromptTemplate",
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"type": "ChatPromptTemplate",
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"baseClasses": [
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"ChatPromptTemplate",
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"BaseChatPromptTemplate",
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"BasePromptTemplate",
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"Runnable"
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],
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"baseClasses": ["ChatPromptTemplate", "BaseChatPromptTemplate", "BasePromptTemplate", "Runnable"],
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"category": "Prompts",
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"description": "Schema to represent a chat prompt",
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"inputParams": [
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@ -385,11 +369,11 @@
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},
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{
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"width": 300,
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"height": 329,
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"height": 328,
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"id": "structuredOutputParser_0",
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"position": {
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"x": 498.2326128526694,
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"y": 566.5473204649535
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"x": 170.3869571939727,
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"y": 343.9298288967859
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},
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"type": "customNode",
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"data": {
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@ -398,11 +382,7 @@
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"version": 1,
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"name": "structuredOutputParser",
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"type": "StructuredOutputParser",
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"baseClasses": [
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"StructuredOutputParser",
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"BaseLLMOutputParser",
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"Runnable"
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],
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"baseClasses": ["StructuredOutputParser", "BaseLLMOutputParser", "Runnable"],
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"category": "Output Parsers",
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"description": "Parse the output of an LLM call into a given (JSON) structure.",
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"inputParams": [
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@ -415,20 +395,61 @@
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"id": "structuredOutputParser_0-input-autofixParser-boolean"
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},
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{
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"label": "Example JSON",
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"name": "exampleJson",
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"type": "string",
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"description": "Example JSON structure for LLM to return",
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"rows": 10,
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"default": "{\"answer\": \"the answer\", \"followupQuestions\": [\"question1\", \"question2\"]}",
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"label": "JSON Structure",
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"name": "jsonStructure",
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"type": "datagrid",
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"description": "JSON structure for LLM to return",
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"datagrid": [
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{
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"field": "property",
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"headerName": "Property",
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"editable": true
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},
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{
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"field": "type",
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"headerName": "Type",
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"type": "singleSelect",
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"valueOptions": ["string", "number", "boolean"],
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"editable": true
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},
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{
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"field": "description",
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"headerName": "Description",
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"editable": true,
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"flex": 1
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}
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],
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"default": [
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{
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"property": "answer",
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"type": "string",
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"description": "answer to the user's question"
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},
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{
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"property": "source",
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"type": "string",
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"description": "sources used to answer the question, should be websites"
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}
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],
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"additionalParams": true,
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"id": "structuredOutputParser_0-input-exampleJson-string"
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"id": "structuredOutputParser_0-input-jsonStructure-datagrid"
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}
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],
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"inputAnchors": [],
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"inputs": {
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"autofixParser": true,
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"exampleJson": "{\"answer\": \"the answer\", \"followupQuestions\": [\"question1\", \"question2\"]}"
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"jsonStructure": [
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{
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"property": "answer",
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"type": "string",
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"description": "answer to the user's question"
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},
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{
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"property": "source",
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"type": "string",
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"description": "sources used to answer the question, should be websites"
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}
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]
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},
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"outputAnchors": [
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{
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@ -442,11 +463,11 @@
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"selected": false
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},
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"selected": false,
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"dragging": false,
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"positionAbsolute": {
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"x": 498.2326128526694,
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"y": 566.5473204649535
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}
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"x": 170.3869571939727,
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"y": 343.9298288967859
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},
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"dragging": false
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}
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],
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"edges": [
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@ -478,7 +499,10 @@
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"target": "llmChain_0",
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"targetHandle": "llmChain_0-input-outputParser-BaseLLMOutputParser",
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"type": "buttonedge",
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"id": "structuredOutputParser_0-structuredOutputParser_0-output-structuredOutputParser-StructuredOutputParser|BaseLLMOutputParser|Runnable-llmChain_0-llmChain_0-input-outputParser-BaseLLMOutputParser"
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"id": "structuredOutputParser_0-structuredOutputParser_0-output-structuredOutputParser-StructuredOutputParser|BaseLLMOutputParser|Runnable-llmChain_0-llmChain_0-input-outputParser-BaseLLMOutputParser",
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"data": {
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"label": ""
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}
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}
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]
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}
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}
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