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feat: Add structured JSON output support to Agent Node (#5470) 

* feat: Add structured JSON output support to Agent Node

- Add agentStructuredOutput input parameter matching LLM Node structure
- Implement configureStructuredOutput method to convert schema to Zod
- Add createZodSchemaFromJSON helper for complex JSON schemas
- Configure structured output before binding tools (required order)
- Disable streaming when structured output is enabled
- Extract structured fields in prepareOutputObject method
- Resolves issue #5256

* lint fix

* add structured output to Agent node

* add structured output to Agent node

---------

Co-authored-by: Henry <hzj94@hotmail.com>
This commit is contained in:
Siddharth Chauhan 2025-11-26 01:22:49 +05:30 committed by GitHub
parent 4d79653741
commit 1f3f7a7194
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GPG Key ID: B5690EEEBB952194
4 changed files with 355 additions and 180 deletions
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214
packages/components/nodes/agentflow/Agent/Agent.ts
View File

@ -28,7 +28,13 @@ import {
replaceBase64ImagesWithFileReferences,
updateFlowState
} from '../utils'
import { convertMultiOptionsToStringArray, getCredentialData, getCredentialParam, processTemplateVariables } from '../../../src/utils'
import {
convertMultiOptionsToStringArray,
getCredentialData,
getCredentialParam,
processTemplateVariables,
configureStructuredOutput
} from '../../../src/utils'
import { addSingleFileToStorage } from '../../../src/storageUtils'
import fetch from 'node-fetch'
@ -394,6 +400,108 @@ class Agent_Agentflow implements INode {
],
default: 'userMessage'
},
{
label: 'JSON Structured Output',
name: 'agentStructuredOutput',
description: 'Instruct the Agent to give output in a JSON structured schema',
type: 'array',
optional: true,
acceptVariable: true,
array: [
{
label: 'Key',
name: 'key',
type: 'string'
},
{
label: 'Type',
name: 'type',
type: 'options',
options: [
{
label: 'String',
name: 'string'
},
{
label: 'String Array',
name: 'stringArray'
},
{
label: 'Number',
name: 'number'
},
{
label: 'Boolean',
name: 'boolean'
},
{
label: 'Enum',
name: 'enum'
},
{
label: 'JSON Array',
name: 'jsonArray'
}
]
},
{
label: 'Enum Values',
name: 'enumValues',
type: 'string',
placeholder: 'value1, value2, value3',
description: 'Enum values. Separated by comma',
optional: true,
show: {
'agentStructuredOutput[$index].type': 'enum'
}
},
{
label: 'JSON Schema',
name: 'jsonSchema',
type: 'code',
placeholder: `{
"answer": {
"type": "string",
"description": "Value of the answer"
},
"reason": {
"type": "string",
"description": "Reason for the answer"
},
"optional": {
"type": "boolean"
},
"count": {
"type": "number"
},
"children": {
"type": "array",
"items": {
"type": "object",
"properties": {
"value": {
"type": "string",
"description": "Value of the children's answer"
}
}
}
}
}`,
description: 'JSON schema for the structured output',
optional: true,
hideCodeExecute: true,
show: {
'agentStructuredOutput[$index].type': 'jsonArray'
}
},
{
label: 'Description',
name: 'description',
type: 'string',
placeholder: 'Description of the key'
}
]
},
{
label: 'Update Flow State',
name: 'agentUpdateState',
@ -770,6 +878,7 @@ class Agent_Agentflow implements INode {
const memoryType = nodeData.inputs?.agentMemoryType as string
const userMessage = nodeData.inputs?.agentUserMessage as string
const _agentUpdateState = nodeData.inputs?.agentUpdateState
const _agentStructuredOutput = nodeData.inputs?.agentStructuredOutput
const agentMessages = (nodeData.inputs?.agentMessages as unknown as ILLMMessage[]) ?? []
// Extract runtime state and history
@ -795,6 +904,8 @@ class Agent_Agentflow implements INode {
const llmWithoutToolsBind = (await newLLMNodeInstance.init(newNodeData, '', options)) as BaseChatModel
let llmNodeInstance = llmWithoutToolsBind
const isStructuredOutput = _agentStructuredOutput && Array.isArray(_agentStructuredOutput) && _agentStructuredOutput.length > 0
const agentToolsBuiltInOpenAI = convertMultiOptionsToStringArray(nodeData.inputs?.agentToolsBuiltInOpenAI)
if (agentToolsBuiltInOpenAI && agentToolsBuiltInOpenAI.length > 0) {
for (const tool of agentToolsBuiltInOpenAI) {
@ -953,7 +1064,7 @@ class Agent_Agentflow implements INode {
// Initialize response and determine if streaming is possible
let response: AIMessageChunk = new AIMessageChunk('')
const isLastNode = options.isLastNode as boolean
const isStreamable = isLastNode && options.sseStreamer !== undefined && modelConfig?.streaming !== false
const isStreamable = isLastNode && options.sseStreamer !== undefined && modelConfig?.streaming !== false && !isStructuredOutput
// Start analytics
if (analyticHandlers && options.parentTraceIds) {
@ -1002,7 +1113,8 @@ class Agent_Agentflow implements INode {
llmWithoutToolsBind,
isStreamable,
isLastNode,
iterationContext
iterationContext,
isStructuredOutput
})
response = result.response
@ -1031,7 +1143,14 @@ class Agent_Agentflow implements INode {
}
} else {
if (isStreamable) {
response = await this.handleStreamingResponse(sseStreamer, llmNodeInstance, messages, chatId, abortController)
response = await this.handleStreamingResponse(
sseStreamer,
llmNodeInstance,
messages,
chatId,
abortController,
isStructuredOutput
)
} else {
response = await llmNodeInstance.invoke(messages, { signal: abortController?.signal })
}
@ -1053,7 +1172,8 @@ class Agent_Agentflow implements INode {
llmNodeInstance,
isStreamable,
isLastNode,
iterationContext
iterationContext,
isStructuredOutput
})
response = result.response
@ -1080,8 +1200,9 @@ class Agent_Agentflow implements INode {
sseStreamer.streamArtifactsEvent(chatId, flatten(artifacts))
}
}
} else if (!humanInput && !isStreamable && isLastNode && sseStreamer) {
} else if (!humanInput && !isStreamable && isLastNode && sseStreamer && !isStructuredOutput) {
// Stream whole response back to UI if not streaming and no tool calls
// Skip this if structured output is enabled - it will be streamed after conversion
let finalResponse = ''
if (response.content && Array.isArray(response.content)) {
finalResponse = response.content.map((item: any) => item.text).join('\n')
@ -1159,6 +1280,23 @@ class Agent_Agentflow implements INode {
finalResponse = await this.processSandboxLinks(finalResponse, options.baseURL, options.chatflowid, chatId)
}
// If is structured output, then invoke LLM again with structured output at the very end after all tool calls
if (isStructuredOutput) {
llmNodeInstance = configureStructuredOutput(llmNodeInstance, _agentStructuredOutput)
const prompt = 'Convert the following response to the structured output format: ' + finalResponse
response = await llmNodeInstance.invoke(prompt, { signal: abortController?.signal })
if (typeof response === 'object') {
finalResponse = '```json\n' + JSON.stringify(response, null, 2) + '\n```'
} else {
finalResponse = response
}
if (isLastNode && sseStreamer) {
sseStreamer.streamTokenEvent(chatId, finalResponse)
}
}
const output = this.prepareOutputObject(
response,
availableTools,
@ -1171,7 +1309,8 @@ class Agent_Agentflow implements INode {
artifacts,
additionalTokens,
isWaitingForHumanInput,
fileAnnotations
fileAnnotations,
isStructuredOutput
)
// End analytics tracking
@ -1561,13 +1700,14 @@ class Agent_Agentflow implements INode {
llmNodeInstance: BaseChatModel,
messages: BaseMessageLike[],
chatId: string,
abortController: AbortController
abortController: AbortController,
isStructuredOutput: boolean = false
): Promise<AIMessageChunk> {
let response = new AIMessageChunk('')
try {
for await (const chunk of await llmNodeInstance.stream(messages, { signal: abortController?.signal })) {
if (sseStreamer) {
if (sseStreamer && !isStructuredOutput) {
let content = ''
if (typeof chunk === 'string') {
@ -1610,7 +1750,8 @@ class Agent_Agentflow implements INode {
artifacts: any[],
additionalTokens: number = 0,
isWaitingForHumanInput: boolean = false,
fileAnnotations: any[] = []
fileAnnotations: any[] = [],
isStructuredOutput: boolean = false
): any {
const output: any = {
content: finalResponse,
@ -1645,6 +1786,15 @@ class Agent_Agentflow implements INode {
output.responseMetadata = response.response_metadata
}
if (isStructuredOutput && typeof response === 'object') {
const structuredOutput = response as Record<string, any>
for (const key in structuredOutput) {
if (structuredOutput[key] !== undefined && structuredOutput[key] !== null) {
output[key] = structuredOutput[key]
}
}
}
// Add used tools, source documents and artifacts to output
if (usedTools && usedTools.length > 0) {
output.usedTools = flatten(usedTools)
@ -1710,7 +1860,8 @@ class Agent_Agentflow implements INode {
llmNodeInstance,
isStreamable,
isLastNode,
iterationContext
iterationContext,
isStructuredOutput = false
}: {
response: AIMessageChunk
messages: BaseMessageLike[]
@ -1724,6 +1875,7 @@ class Agent_Agentflow implements INode {
isStreamable: boolean
isLastNode: boolean
iterationContext: ICommonObject
isStructuredOutput?: boolean
}): Promise<{
response: AIMessageChunk
usedTools: IUsedTool[]
@ -1803,7 +1955,9 @@ class Agent_Agentflow implements INode {
const toolCallDetails = '```json\n' + JSON.stringify(toolCall, null, 2) + '\n```'
const responseContent = response.content + `\nAttempting to use tool:\n${toolCallDetails}`
response.content = responseContent
sseStreamer?.streamTokenEvent(chatId, responseContent)
if (!isStructuredOutput) {
sseStreamer?.streamTokenEvent(chatId, responseContent)
}
return { response, usedTools, sourceDocuments, artifacts, totalTokens, isWaitingForHumanInput: true }
}
@ -1909,7 +2063,7 @@ class Agent_Agentflow implements INode {
const lastToolOutput = usedTools[0]?.toolOutput || ''
const lastToolOutputString = typeof lastToolOutput === 'string' ? lastToolOutput : JSON.stringify(lastToolOutput, null, 2)
if (sseStreamer) {
if (sseStreamer && !isStructuredOutput) {
sseStreamer.streamTokenEvent(chatId, lastToolOutputString)
}
@ -1938,12 +2092,19 @@ class Agent_Agentflow implements INode {
let newResponse: AIMessageChunk
if (isStreamable) {
newResponse = await this.handleStreamingResponse(sseStreamer, llmNodeInstance, messages, chatId, abortController)
newResponse = await this.handleStreamingResponse(
sseStreamer,
llmNodeInstance,
messages,
chatId,
abortController,
isStructuredOutput
)
} else {
newResponse = await llmNodeInstance.invoke(messages, { signal: abortController?.signal })
// Stream non-streaming response if this is the last node
if (isLastNode && sseStreamer) {
if (isLastNode && sseStreamer && !isStructuredOutput) {
let responseContent = JSON.stringify(newResponse, null, 2)
if (typeof newResponse.content === 'string') {
responseContent = newResponse.content
@ -1978,7 +2139,8 @@ class Agent_Agentflow implements INode {
llmNodeInstance,
isStreamable,
isLastNode,
iterationContext
iterationContext,
isStructuredOutput
})
// Merge results from recursive tool calls
@ -2009,7 +2171,8 @@ class Agent_Agentflow implements INode {
llmWithoutToolsBind,
isStreamable,
isLastNode,
iterationContext
iterationContext,
isStructuredOutput = false
}: {
humanInput: IHumanInput
humanInputAction: Record<string, any> | undefined
@ -2024,6 +2187,7 @@ class Agent_Agentflow implements INode {
isStreamable: boolean
isLastNode: boolean
iterationContext: ICommonObject
isStructuredOutput?: boolean
}): Promise<{
response: AIMessageChunk
usedTools: IUsedTool[]
@ -2226,7 +2390,7 @@ class Agent_Agentflow implements INode {
const lastToolOutput = usedTools[0]?.toolOutput || ''
const lastToolOutputString = typeof lastToolOutput === 'string' ? lastToolOutput : JSON.stringify(lastToolOutput, null, 2)
if (sseStreamer) {
if (sseStreamer && !isStructuredOutput) {
sseStreamer.streamTokenEvent(chatId, lastToolOutputString)
}
@ -2257,12 +2421,19 @@ class Agent_Agentflow implements INode {
}
if (isStreamable) {
newResponse = await this.handleStreamingResponse(sseStreamer, llmNodeInstance, messages, chatId, abortController)
newResponse = await this.handleStreamingResponse(
sseStreamer,
llmNodeInstance,
messages,
chatId,
abortController,
isStructuredOutput
)
} else {
newResponse = await llmNodeInstance.invoke(messages, { signal: abortController?.signal })
// Stream non-streaming response if this is the last node
if (isLastNode && sseStreamer) {
if (isLastNode && sseStreamer && !isStructuredOutput) {
let responseContent = JSON.stringify(newResponse, null, 2)
if (typeof newResponse.content === 'string') {
responseContent = newResponse.content
@ -2297,7 +2468,8 @@ class Agent_Agentflow implements INode {
llmNodeInstance,
isStreamable,
isLastNode,
iterationContext
iterationContext,
isStructuredOutput
})
// Merge results from recursive tool calls

161
packages/components/nodes/agentflow/LLM/LLM.ts
View File

@ -2,9 +2,8 @@ import { BaseChatModel } from '@langchain/core/language_models/chat_models'
import { ICommonObject, IMessage, INode, INodeData, INodeOptionsValue, INodeParams, IServerSideEventStreamer } from '../../../src/Interface'
import { AIMessageChunk, BaseMessageLike, MessageContentText } from '@langchain/core/messages'
import { DEFAULT_SUMMARIZER_TEMPLATE } from '../prompt'
import { z } from 'zod'
import { AnalyticHandler } from '../../../src/handler'
import { ILLMMessage, IStructuredOutput } from '../Interface.Agentflow'
import { ILLMMessage } from '../Interface.Agentflow'
import {
getPastChatHistoryImageMessages,
getUniqueImageMessages,
@ -12,7 +11,7 @@ import {
replaceBase64ImagesWithFileReferences,
updateFlowState
} from '../utils'
import { processTemplateVariables } from '../../../src/utils'
import { processTemplateVariables, configureStructuredOutput } from '../../../src/utils'
import { flatten } from 'lodash'
class LLM_Agentflow implements INode {
@ -452,7 +451,7 @@ class LLM_Agentflow implements INode {
// Configure structured output if specified
const isStructuredOutput = _llmStructuredOutput && Array.isArray(_llmStructuredOutput) && _llmStructuredOutput.length > 0
if (isStructuredOutput) {
llmNodeInstance = this.configureStructuredOutput(llmNodeInstance, _llmStructuredOutput)
llmNodeInstance = configureStructuredOutput(llmNodeInstance, _llmStructuredOutput)
}
// Initialize response and determine if streaming is possible
@ -755,59 +754,6 @@ class LLM_Agentflow implements INode {
}
}
/**
* Configures structured output for the LLM
*/
private configureStructuredOutput(llmNodeInstance: BaseChatModel, llmStructuredOutput: IStructuredOutput[]): BaseChatModel {
try {
const zodObj: ICommonObject = {}
for (const sch of llmStructuredOutput) {
if (sch.type === 'string') {
zodObj[sch.key] = z.string().describe(sch.description || '')
} else if (sch.type === 'stringArray') {
zodObj[sch.key] = z.array(z.string()).describe(sch.description || '')
} else if (sch.type === 'number') {
zodObj[sch.key] = z.number().describe(sch.description || '')
} else if (sch.type === 'boolean') {
zodObj[sch.key] = z.boolean().describe(sch.description || '')
} else if (sch.type === 'enum') {
const enumValues = sch.enumValues?.split(',').map((item: string) => item.trim()) || []
zodObj[sch.key] = z
.enum(enumValues.length ? (enumValues as [string, ...string[]]) : ['default'])
.describe(sch.description || '')
} else if (sch.type === 'jsonArray') {
const jsonSchema = sch.jsonSchema
if (jsonSchema) {
try {
// Parse the JSON schema
const schemaObj = JSON.parse(jsonSchema)
// Create a Zod schema from the JSON schema
const itemSchema = this.createZodSchemaFromJSON(schemaObj)
// Create an array schema of the item schema
zodObj[sch.key] = z.array(itemSchema).describe(sch.description || '')
} catch (err) {
console.error(`Error parsing JSON schema for ${sch.key}:`, err)
// Fallback to generic array of records
zodObj[sch.key] = z.array(z.record(z.any())).describe(sch.description || '')
}
} else {
// If no schema provided, use generic array of records
zodObj[sch.key] = z.array(z.record(z.any())).describe(sch.description || '')
}
}
}
const structuredOutput = z.object(zodObj)
// @ts-ignore
return llmNodeInstance.withStructuredOutput(structuredOutput)
} catch (exception) {
console.error(exception)
return llmNodeInstance
}
}
/**
* Handles streaming response from the LLM
*/
@ -911,107 +857,6 @@ class LLM_Agentflow implements INode {
sseStreamer.streamEndEvent(chatId)
}
/**
* Creates a Zod schema from a JSON schema object
* @param jsonSchema The JSON schema object
* @returns A Zod schema
*/
private createZodSchemaFromJSON(jsonSchema: any): z.ZodTypeAny {
// If the schema is an object with properties, create an object schema
if (typeof jsonSchema === 'object' && jsonSchema !== null) {
const schemaObj: Record<string, z.ZodTypeAny> = {}
// Process each property in the schema
for (const [key, value] of Object.entries(jsonSchema)) {
if (value === null) {
// Handle null values
schemaObj[key] = z.null()
} else if (typeof value === 'object' && !Array.isArray(value)) {
// Check if the property has a type definition
if ('type' in value) {
const type = value.type as string
const description = ('description' in value ? (value.description as string) : '') || ''
// Create the appropriate Zod type based on the type property
if (type === 'string') {
schemaObj[key] = z.string().describe(description)
} else if (type === 'number') {
schemaObj[key] = z.number().describe(description)
} else if (type === 'boolean') {
schemaObj[key] = z.boolean().describe(description)
} else if (type === 'array') {
// If it's an array type, check if items is defined
if ('items' in value && value.items) {
const itemSchema = this.createZodSchemaFromJSON(value.items)
schemaObj[key] = z.array(itemSchema).describe(description)
} else {
// Default to array of any if items not specified
schemaObj[key] = z.array(z.any()).describe(description)
}
} else if (type === 'object') {
// If it's an object type, check if properties is defined
if ('properties' in value && value.properties) {
const nestedSchema = this.createZodSchemaFromJSON(value.properties)
schemaObj[key] = nestedSchema.describe(description)
} else {
// Default to record of any if properties not specified
schemaObj[key] = z.record(z.any()).describe(description)
}
} else {
// Default to any for unknown types
schemaObj[key] = z.any().describe(description)
}
// Check if the property is optional
if ('optional' in value && value.optional === true) {
schemaObj[key] = schemaObj[key].optional()
}
} else if (Array.isArray(value)) {
// Array values without a type property
if (value.length > 0) {
// If the array has items, recursively create a schema for the first item
const itemSchema = this.createZodSchemaFromJSON(value[0])
schemaObj[key] = z.array(itemSchema)
} else {
// Empty array, allow any array
schemaObj[key] = z.array(z.any())
}
} else {
// It's a nested object without a type property, recursively create schema
schemaObj[key] = this.createZodSchemaFromJSON(value)
}
} else if (Array.isArray(value)) {
// Array values
if (value.length > 0) {
// If the array has items, recursively create a schema for the first item
const itemSchema = this.createZodSchemaFromJSON(value[0])
schemaObj[key] = z.array(itemSchema)
} else {
// Empty array, allow any array
schemaObj[key] = z.array(z.any())
}
} else {
// For primitive values (which shouldn't be in the schema directly)
// Use the corresponding Zod type
if (typeof value === 'string') {
schemaObj[key] = z.string()
} else if (typeof value === 'number') {
schemaObj[key] = z.number()
} else if (typeof value === 'boolean') {
schemaObj[key] = z.boolean()
} else {
schemaObj[key] = z.any()
}
}
}
return z.object(schemaObj)
}
// Fallback to any for unknown types
return z.any()
}
}
module.exports = { nodeClass: LLM_Agentflow }

158
packages/components/src/utils.ts
View File

@ -8,6 +8,7 @@ import { cloneDeep, omit, get } from 'lodash'
import TurndownService from 'turndown'
import { DataSource, Equal } from 'typeorm'
import { ICommonObject, IDatabaseEntity, IFileUpload, IMessage, INodeData, IVariable, MessageContentImageUrl } from './Interface'
import { BaseChatModel } from '@langchain/core/language_models/chat_models'
import { AES, enc } from 'crypto-js'
import { AIMessage, HumanMessage, BaseMessage } from '@langchain/core/messages'
import { Document } from '@langchain/core/documents'
@ -1941,3 +1942,160 @@ export async function parseWithTypeConversion<T extends z.ZodTypeAny>(schema: T,
throw e
}
}
/**
* Configures structured output for the LLM using Zod schema
* @param {BaseChatModel} llmNodeInstance - The LLM instance to configure
* @param {any[]} structuredOutput - Array of structured output schema definitions
* @returns {BaseChatModel} - The configured LLM instance
*/
export const configureStructuredOutput = (llmNodeInstance: BaseChatModel, structuredOutput: any[]): BaseChatModel => {
try {
const zodObj: ICommonObject = {}
for (const sch of structuredOutput) {
if (sch.type === 'string') {
zodObj[sch.key] = z.string().describe(sch.description || '')
} else if (sch.type === 'stringArray') {
zodObj[sch.key] = z.array(z.string()).describe(sch.description || '')
} else if (sch.type === 'number') {
zodObj[sch.key] = z.number().describe(sch.description || '')
} else if (sch.type === 'boolean') {
zodObj[sch.key] = z.boolean().describe(sch.description || '')
} else if (sch.type === 'enum') {
const enumValues = sch.enumValues?.split(',').map((item: string) => item.trim()) || []
zodObj[sch.key] = z
.enum(enumValues.length ? (enumValues as [string, ...string[]]) : ['default'])
.describe(sch.description || '')
} else if (sch.type === 'jsonArray') {
const jsonSchema = sch.jsonSchema
if (jsonSchema) {
try {
// Parse the JSON schema
const schemaObj = JSON.parse(jsonSchema)
// Create a Zod schema from the JSON schema
const itemSchema = createZodSchemaFromJSON(schemaObj)
// Create an array schema of the item schema
zodObj[sch.key] = z.array(itemSchema).describe(sch.description || '')
} catch (err) {
console.error(`Error parsing JSON schema for ${sch.key}:`, err)
// Fallback to generic array of records
zodObj[sch.key] = z.array(z.record(z.any())).describe(sch.description || '')
}
} else {
// If no schema provided, use generic array of records
zodObj[sch.key] = z.array(z.record(z.any())).describe(sch.description || '')
}
}
}
const structuredOutputSchema = z.object(zodObj)
// @ts-ignore
return llmNodeInstance.withStructuredOutput(structuredOutputSchema)
} catch (exception) {
console.error(exception)
return llmNodeInstance
}
}
/**
* Creates a Zod schema from a JSON schema object
* @param {any} jsonSchema - The JSON schema object
* @returns {z.ZodTypeAny} - A Zod schema
*/
export const createZodSchemaFromJSON = (jsonSchema: any): z.ZodTypeAny => {
// If the schema is an object with properties, create an object schema
if (typeof jsonSchema === 'object' && jsonSchema !== null) {
const schemaObj: Record<string, z.ZodTypeAny> = {}
// Process each property in the schema
for (const [key, value] of Object.entries(jsonSchema)) {
if (value === null) {
// Handle null values
schemaObj[key] = z.null()
} else if (typeof value === 'object' && !Array.isArray(value)) {
// Check if the property has a type definition
if ('type' in value) {
const type = value.type as string
const description = ('description' in value ? (value.description as string) : '') || ''
// Create the appropriate Zod type based on the type property
if (type === 'string') {
schemaObj[key] = z.string().describe(description)
} else if (type === 'number') {
schemaObj[key] = z.number().describe(description)
} else if (type === 'boolean') {
schemaObj[key] = z.boolean().describe(description)
} else if (type === 'array') {
// If it's an array type, check if items is defined
if ('items' in value && value.items) {
const itemSchema = createZodSchemaFromJSON(value.items)
schemaObj[key] = z.array(itemSchema).describe(description)
} else {
// Default to array of any if items not specified
schemaObj[key] = z.array(z.any()).describe(description)
}
} else if (type === 'object') {
// If it's an object type, check if properties is defined
if ('properties' in value && value.properties) {
const nestedSchema = createZodSchemaFromJSON(value.properties)
schemaObj[key] = nestedSchema.describe(description)
} else {
// Default to record of any if properties not specified
schemaObj[key] = z.record(z.any()).describe(description)
}
} else {
// Default to any for unknown types
schemaObj[key] = z.any().describe(description)
}
// Check if the property is optional
if ('optional' in value && value.optional === true) {
schemaObj[key] = schemaObj[key].optional()
}
} else if (Array.isArray(value)) {
// Array values without a type property
if (value.length > 0) {
// If the array has items, recursively create a schema for the first item
const itemSchema = createZodSchemaFromJSON(value[0])
schemaObj[key] = z.array(itemSchema)
} else {
// Empty array, allow any array
schemaObj[key] = z.array(z.any())
}
} else {
// It's a nested object without a type property, recursively create schema
schemaObj[key] = createZodSchemaFromJSON(value)
}
} else if (Array.isArray(value)) {
// Array values
if (value.length > 0) {
// If the array has items, recursively create a schema for the first item
const itemSchema = createZodSchemaFromJSON(value[0])
schemaObj[key] = z.array(itemSchema)
} else {
// Empty array, allow any array
schemaObj[key] = z.array(z.any())
}
} else {
// For primitive values (which shouldn't be in the schema directly)
// Use the corresponding Zod type
if (typeof value === 'string') {
schemaObj[key] = z.string()
} else if (typeof value === 'number') {
schemaObj[key] = z.number()
} else if (typeof value === 'boolean') {
schemaObj[key] = z.boolean()
} else {
schemaObj[key] = z.any()
}
}
}
return z.object(schemaObj)
}
// Fallback to any for unknown types
return z.any()
}

2
packages/ui/src/ui-component/input/suggestionOption.js
View File

@ -112,7 +112,7 @@ export const suggestionOptions = (
category: 'Node Outputs'
})
const structuredOutputs = nodeData?.inputs?.llmStructuredOutput ?? []
const structuredOutputs = nodeData?.inputs?.llmStructuredOutput ?? nodeData?.inputs?.agentStructuredOutput ?? []
if (structuredOutputs && structuredOutputs.length > 0) {
structuredOutputs.forEach((item) => {
defaultItems.unshift({