[Python] openai structured outputs schema with condition

I’m trying to use openai structured outputs with a JSON Schema, such that: • If part1 is "yes", then part2 must be present (required). • If part1 is "no", then part2 must not be included at all.

Below is my code, I’m attempting to enforce the conditional requirement in the allOf section. However, openai will not accept this schema because of the "allOf" part.

How can I fix (or confirm) the JSON Schema definition to correctly handle this conditional requirement?

import openai
import json
import jsonschema
from dotenv import load_dotenv
import os

load_dotenv()
api_key = os.getenv("API_KEY")
api_version = os.getenv("API_VERSION")
base_url = os.getenv("API_BASE_URL_4o")

# 1. Configure OpenAI credentials
openai.api_key = api_key
openai.api_version = api_version
openai.api_type = "azure"
openai.base_url = base_url

# 2. Define the function schema
answer_question_function = {
"name": "answer_question",
"description": "Answers user question with conditional parts",
"parameters": {
"type": "object",
"properties": {
"part1": {
"type": "string",
"enum": ["yes", "no"],
"description": "First part answer"
},
"part2": {
"type": "string",
"enum": ["yes", "no"],
"description": "Second part answer; required only if part1 is yes"
}
},
"required": ["part1"],
"allOf": [
{
"if": {
"properties": {
"part1": {"const": "yes"}
}
},
"then": {
"required": ["part2"]
}
},
{
"if": {
"properties": {
"part1": {"const": "no"}
}
},
"then": {
"not": {"required": ["part2"]}
}
}
]
}
}

# 3. Write a helper function to validate the JSON result against our schema
def validate_function_call_arguments(args):
schema = answer_question_function["parameters"]
jsonschema.validate(instance=args, schema=schema)

# 4. E2E test function
def run_e2e_test(user_prompt):
"""
Sends a prompt to the model, requests a function call,
and validates the JSON arguments returned.
"""

load_dotenv()
api_key = os.getenv("API_KEY")
api_version = os.getenv("API_VERSION")
base_url = os.getenv("API_BASE_URL_4o")

openai.api_key = api_key
openai.api_version = api_version
openai.api_type = "azure"
openai.base_url = base_url

try:
response = openai.chat.completions.create(
model="gpt-4o",
messages=[
{
"role": "user",
"content": user_prompt
}
],
response_format={
"type": "json_schema",
"json_schema": {
"name": "answer_question",
"schema": answer_question_function["parameters"]
}
},
)

# Check if it's a function call:
choice = response["choices"][0]

if choice["finish_reason"] == "function_call":
function_call = choice["message"]["function_call"]
function_name = function_call["name"]
arguments_json = function_call["arguments"]

print(f"Function called: {function_name}")
print(f"Raw arguments: {arguments_json}")

# Convert the JSON string into a Python dict
arguments = json.loads(arguments_json)

# Validate
validate_function_call_arguments(arguments)
print("✅ JSON arguments valid against the schema.")
print(f"Final arguments object: {arguments}")

else:
# If no function call was made, print the plain text response
print("No function call. Text response from model:")
print(choice["message"]["content"])

except jsonschema.ValidationError as e:
print("❌ JSON arguments failed validation:")
print(str(e))
except Exception as e:
print("❌ Something went wrong:")
print(str(e))

# 5. Run a few test scenarios
if __name__ == "__main__":
print("===== TEST: Expecting part1 = yes, then part2 is required =====")
run_e2e_test("Should part1 be yes? If so, give me part2 too.")

print("\n===== TEST: Expecting part1 = no, then part2 should not appear =====")
run_e2e_test("Should part1 be no? Then we don’t want part2.")
print()

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