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Description
Description of the bug:
When using the google-genai Python SDK to submit a batch job for image generation (using the gemini-3-pro-image-preview model), the SDK throws a Pydantic validation error if image_config is included in the generation_config.
According to the official documentation and Google Colab examples, image_config (containing aspect_ratio and image_size) should be supported. However, the SDK's Pydantic model seems to reject these fields as "extra inputs".
Actual vs expected behavior:
Python
from google import genai
client = genai.Client(api_key='YOUR_API_KEY')
Basic inline request structure following the docs
inline_requests = [
{
"contents": [{
"parts": [
{"text": "Transform this image into pixel art."},
{"inline_data": {"mime_type": "image/jpeg", "data": "BASE64_DATA..."}}
],
}],
"generation_config": {
"response_modalities": ["IMAGE"],
"image_config": {
"aspect_ratio": "16:9",
"image_size": "2K"
}
}
}
]
client.batches.create(
model="models/gemini-3-pro-image-preview",
src=inline_requests,
config={'display_name': 'test-job'}
)
Expected behavior The batch job should be created successfully without validation errors, as image_config is a documented feature for the Nano-Banana model.
Actual behavior (Error Message)
Plaintext
ValidationError: 1 validation error for BatchJobSource
inlined_requests.0.generation_config
Extra inputs are not permitted [type=extra_forbidden, input_value={'response_modalities': ['IMAGE'], 'image_config': {'aspect_ratio': '16:9', 'image_size': '2K'}}, input_type=dict]
Any other information you'd like to share?
No response