Structured outputs enable a model to generate output that always adheres to a specific schema. For example, a model may be provided with a response schema to ensure that the response produces valid JSON. All open models available on the Vertex AI Model as a Service (MaaS) support structured outputs.
For more conceptual information about the structured output capability, see Introduction to structured output.
Use structured outputs
The following use case sets a response schema that ensures that the model output is a JSON object with the following properties: name, date, and participants. The Python code uses the OpenAI SDK and Pydantic objects to generate the JSON schema.
from pydantic import BaseModel
from openai import OpenAI
client = OpenAI()
class CalendarEvent(BaseModel):
name: str
date: str
participants: list[str]
completion = client.beta.chat.completions.parse(
model="MODEL_NAME",
messages=[
{"role": "system", "content": "Extract the event information."},
{"role": "user", "content": "Alice and Bob are going to a science fair on Friday."},
],
response_format=CalendarEvent,
)
print(completion.choices[0].message.parsed)
The model output will adhere to the following JSON schema:
{ "name": STRING, "date": STRING, "participants": [STRING] }
When provided the prompt, "Alice and Bob are going to a science fair on Friday", the model could produce the following response:
{
"name": "science fair",
"date": "Friday",
"participants": [
"Alice",
"Bob"
]
}
Detailed example
The following code is an example of a recursive schema. The UI
class contains
a list of children
, which can also be of the UI
class.
from pydantic import BaseModel
from openai import OpenAI
from enum import Enum
from typing import List
client = OpenAI()
class UIType(str, Enum):
div = "div"
button = "button"
header = "header"
section = "section"
field = "field"
form = "form"
class Attribute(BaseModel):
name: str
value: str
class UI(BaseModel):
type: UIType
label: str
children: List["UI"]
attributes: List[Attribute]
UI.model_rebuild() # This is required to enable recursive types
class Response(BaseModel):
ui: UI
completion = client.beta.chat.completions.parse(
model="MODEL_NAME",
messages=[
{"role": "system", "content": "You are a UI generator AI. Convert the user input into a UI."},
{"role": "user", "content": "Make a User Profile Form"}
],
response_format=Response,
)
print(completion.choices[0].message.parsed)
The model output will adhere to the schema of the Pydantic object specified in the previous snippet. In this example, the model could generate the following UI form:
Form
Input
Name
Email
Age
A response could look like the following:
ui = UI(
type=UIType.div,
label='Form',
children=[
UI(
type=UIType.div,
label='Input',
children=[],
attributes=[
Attribute(name='label', value='Name')
]
),
UI(
type=UIType.div,
label='Input',
children=[],
attributes=[
Attribute(name='label', value='Email')
]
),
UI(
type=UIType.div,
label='Input',
children=[],
attributes=[
Attribute(name='label', value='Age')
]
)
],
attributes=[
Attribute(name='name', value='John Doe'),
Attribute(name='email', value='john.doe@example.com'),
Attribute(name='age', value='30')
]
)