# How can I define a Pydantic schema for heterogeneous Node-RED workflows when using OpenAI structured outputs?
**URL:** https://discourse.nodered.org/t/how-can-i-define-a-pydantic-schema-for-heterogeneous-node-red-workflows-when-using-openai-structured-outputs/99352
**Category:** General
**Created:** [11 October 2025 15:05 UTC](https://discourse.nodered.org/t/how-can-i-define-a-pydantic-schema-for-heterogeneous-node-red-workflows-when-using-openai-structured-outputs/99352 "2025-10-11T15:05:33Z")
**Posts on this page:** 2
**Page:** 1
### Author:  [@ashfaq92](https://discourse.nodered.org/u/ashfaq92)
#### Post date: [11 October 2025 15:05 UTC](https://discourse.nodered.org/t/how-can-i-define-a-pydantic-schema-for-heterogeneous-node-red-workflows-when-using-openai-structured-outputs/99352/1 "2025-10-11T15:05:33Z")
Hi, I am new to Node-RED. I have a question where I needed help, I posted this question on [stackoverflow](https://stackoverflow.com/q/79788036), but here I paste again:
I’m experimenting with generating _Node-RED workflows_ using an LLM. As expected, the unstructured JSON responses are often messy or invalid.
To improve reliability, I’m trying to use OpenAI’s `structured_output` feature. It works nicely with simple, fixed schemas — for example:
```auto
from openai import OpenAI
from pydantic import BaseModel
client = OpenAI()
class CalendarEvent(BaseModel):
name: str
date: str
participants: list[str]
response = client.responses.parse(
model="gpt-4o-2024-08-06",
input=[
{"role": "system", "content": "Extract the event information."},
{"role": "user", "content": "Alice and Bob are going to a science fair on Friday."},
],
text_format=CalendarEvent,
)
event = response.output_parsed
```
However, in my case, the target structure — a _Node-RED flow_ — is much more complex and heterogeneous.
A Node-RED flow (or subflow) can contain many types of nodes, each with its own attributes. The [Node-RED admin API docs](https://nodered.org/docs/api/admin/types) describe the general structure, e.g.:
```auto
{
"id": "1234",
"label": "Sheet1",
"nodes": [...],
"configs": [...],
"subflows": [...]
}
```
My question is:
_How should I define a Pydantic model (or a hierarchy of models) that can represent this flexible workflow structure, so that an LLM’s structured output can conform to it?_
I understand that each `node` type may have its own schema, but I’m not sure how to model this polymorphism in a way that still works well with OpenAI’s `structured_output` or `responses.parse`.
Any examples or design patterns for handling this kind of heterogeneous JSON structure would be appreciated.
---
### Author:  [@system](https://discourse.nodered.org/u/system)
#### Post date: [9 January 2026 15:06 UTC](https://discourse.nodered.org/t/how-can-i-define-a-pydantic-schema-for-heterogeneous-node-red-workflows-when-using-openai-structured-outputs/99352/2 "2026-01-09T15:06:02Z")
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