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

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* 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
4 changed files with 355 additions and 180 deletions
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packages/components/nodes/agentflow/LLM/LLM.ts
+3 -158
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 }