I’m using the following response_schema:
"response_schema": {
"type": "ARRAY",
"items": {
"one_of": [
{
"type": "OBJECT",
"properties": {
"stem": {"type": "STRING"}
},
"required": "stem",
},
{
"type": "OBJECT",
"properties": {
"stimuli": {"type": "STRING"}
},
"required": "stimuli",
}
]
}
}
And I’m getting the following error:
GenerateContentRequest.generation_config.response_schema.items.type: must be specified when not using one_of
But as you can see, I’m already using one_of. What I’m doing wrong? Does Gemini API even support oneOf feature of json schema?
3 Likes
Hi,
Welcome to the forum.
Hm, it looks like your schema is missing a closing square bracket “]” to close the “oneOf” array.
Hi, my bad, I lost it during formatting in this post, thnak you for noticiing. But the issue stays the same.
It’s relatively easy to generate an exception:
google.protobuf.json_format.ParseError: Message type "google.cloud.aiplatform.v1beta1.Schema" has no field named "$defs" at "Schema".
Available Fields(except extensions): "['type', 'format', 'title', 'description', 'nullable', 'default', 'items', 'minItems', 'maxItems', 'enum', 'properties', 'propertyOrdering', 'required', 'minProperties', 'maxProperties', 'minimum', 'maximum', 'minLength', 'maxLength', 'pattern', 'example', 'anyOf']"
It kindly provides all fields interpreted, and oneOf is not invited to this party.
3 Likes
Thank you for the additional information 
Error message you posted mentions any_of as allowed option. I tried it and the result error the same as when I tried one_of:
import requests
url = "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-pro:generateContent"
api_key = self.api_key # Replace with your actual API key
headers = {
"Content-Type": "application/json"
}
payload = {
"contents": [{
"parts": [
{"text": "Generate some questions"}
]
}],
"generationConfig": {
"response_mime_type": "application/json",
"response_schema": {
"type": "ARRAY",
"items": {
"any_of": [
{
"type": "OBJECT",
"properties": {
"stem": {"type": "STRING"}
},
"required": "stem",
},
{
"type": "OBJECT",
"properties": {
"stimuli": {"type": "STRING"}
},
"required": "stimuli",
}
]
}
}
}
}
response = requests.post(url, headers=headers, params={"key": api_key}, json=payload)
{'error': {'code': 400, 'message': '* GenerateContentRequest.generation_config.response_schema.items.type: must be specified when not using one_of\n', 'status': 'INVALID_ARGUMENT'}}
I tried to name the field anyOf too, no difference.
Does it mean, that it’s impossible to get a list of different types from Gemini API?
Looks like Vertex AI docs are misleading. AnyOf is not supported. I thought it’s only issue with GenAI, but its same for all forms of accessing Gemini. It is a significant downside comparing to OpenAI
2 Likes
that really “Modified by moderator”. is there a known workaround? I guess you could define a separate function for each type in anyOf but that is just ridiculous.
Missing support for anyOf is just obscene
2 Likes
@GUNAND_MAYANGLAMBAM would you know if support for this is on your roadmap? this info would be really helpful
1 Like
@GUNAND_MAYANGLAMBAM i saw your thumbs up reaction, so I take it that this support is on your roadmap. can you also kindly provide us with an ETA? anyOf support is extremely critical for my use cases
Hey @dabbbulaaax , I can’t provide an ETA, but I have escalated this issue to the team.
@GUNAND_MAYANGLAMBAM appreciate it! pls keep us up to date
@GUNAND_MAYANGLAMBAM congrats on the GA launch of gemini 2.0 flash! Very excited to use it but cant until anyOf is supported. Would you happen to have any updates?
Also a blocker for us. We want to move some of our function calling workflows to Gemini and our schemas use anyOf / oneOf.
Having reliable structured output is a must have for any production ready application with LLMs. The anyOf type absolutely needs to be supported. It is quite misleading that anyOf is claimed to be supported here:
Hope this can be resolved soon.
1 Like
thats a documentation for vertex AI. AFAIK, vertex AI and gemini AI are separate products
@dabbbulaaax Thanks for the comment, you are in fact correct, the anyOf type is supported with vertex ai.
Here’s a working example:
# /// script
# requires-python = ">=3.13"
# dependencies = [
# "google-genai",
# ]
# ///
from google import genai
from google.genai.types import GenerateContentConfig
from pydantic import BaseModel
client = genai.Client(vertexai=True)
model_id = "gemini-2.0-flash-001"
class A(BaseModel):
a: str
class B(BaseModel):
b: int
class C(BaseModel):
value: A | B
response = client.models.generate_content(
model=model_id,
contents="The number is 42",
config=GenerateContentConfig(
response_mime_type="application/json",
response_schema=C,
),
)
print(response.text)
Note that it fails if you put client = genai.Client(vertexai=False).
@Vincent_Min if you do client = genai.Client(vertexai=True), does your billing and rate limits go through vertex AI or gemini ai?
@GUNAND_MAYANGLAMBAM do you happen to have any updates on this? I cant use Gemini through Vertex AI because, unlike Google AI Studio, Vertex AI does not guarantee rate limits (it uses a dynamic shared quota).
1 Like
@GUNAND_MAYANGLAMBAM hi, would you happen to have any updates?
Hi,
anyOf has been added to the Schema definition. Maybe this already helps?
Cheers.