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Merge pull request #40074 from mihidumh/fix/mai-image-unsupported-params

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fix(azure_ai): reject unsupported n and size params on MAI image models
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Mateo Wang 2026-09-09 19:11:11 -07:00 • committed by GitHub
commit 1d18b61e3e
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6 changed files with 238 additions and 135 deletions
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2
litellm/llms/azure_ai/image_edit/__init__.py
View file

@ -23,7 +23,7 @@ def get_azure_ai_image_edit_config(model: str) -> BaseImageEditConfig:
"""
Get the appropriate image edit config for an Azure AI model.
- MAI models use /mai/v1/images/edits with multipart form data and size
- MAI models use /mai/v1/images/edits with multipart form data
- FLUX 2 models use JSON with base64 image
- FLUX 1 models use multipart/form-data
"""

62
litellm/llms/azure_ai/image_edit/mai_transformation.py
View file

@ -1,4 +1,4 @@
from typing import TYPE_CHECKING, Any, Final, cast
from typing import TYPE_CHECKING, Any, Final
import httpx
from httpx._types import RequestFiles
@ -13,7 +13,6 @@ from litellm.llms.azure_ai.image_generation.mai_transformation import (
from litellm.llms.openai.common_utils import OpenAIError
from litellm.llms.openai.image_edit.transformation import OpenAIImageEditConfig
from litellm.secret_managers.main import get_secret_str
from litellm.types.images.main import ImageEditOptionalRequestParams
from litellm.types.llms.openai import FileTypes
from litellm.types.router import GenericLiteLLMParams
from litellm.types.utils import ImageResponse
@ -26,65 +25,8 @@ if TYPE_CHECKING:
class AzureFoundryMAIImageEditConfig(OpenAIImageEditConfig):
"""Azure AI Foundry MAI image editing (e.g. MAI-Image-2.5)."""
DEFAULT_SIZE = "1024x1024"
def get_supported_openai_params(self, model: str) -> list:
return ["prompt", "image", "model", "n", "size"]
def map_openai_params(
self,
image_edit_optional_params: ImageEditOptionalRequestParams,
model: str,
drop_params: bool,
) -> dict:
optional_params: Final[dict[str, Any]] = {}
supported_params: Final = self.get_supported_openai_params(model)
for key, value in dict(image_edit_optional_params).items():
if value is None or key in optional_params:
continue
if key in supported_params:
if key == "size" and value:
size_param = cast(str, value)
self._validate_size_param(size_param)
optional_params[key] = size_param
else:
optional_params[key] = value
elif not drop_params:
raise ValueError(
f"Parameter {key} is not supported for model {model}. "
f"Supported parameters are {supported_params}. "
f"Set drop_params=True to drop unsupported parameters."
)
if "size" not in optional_params:
optional_params["size"] = self.DEFAULT_SIZE
return optional_params
def _validate_size_param(self, size: str) -> None:
known_sizes: Final = {
"1024x1024",
"1792x1024",
"1024x1792",
"512x512",
"256x256",
}
if size in known_sizes:
return
if "x" in size:
try:
tuple(map(int, size.lower().split("x", 1)))
return
except ValueError:
raise ValueError(f"Invalid size format: '{size}'. Expected format 'WIDTHxHEIGHT' (e.g., '1024x1024').")
raise ValueError(
f"Unsupported size value: '{size}'. Use a known size (e.g., '1024x1024') or a custom 'WIDTHxHEIGHT' string."
)
return ["prompt", "image", "model", "n"]
def validate_environment(
self,

67
litellm/llms/azure_ai/image_generation/mai_transformation.py
View file

@ -2,6 +2,7 @@ from typing import TYPE_CHECKING, Any, Final
import httpx
from litellm.exceptions import UnsupportedParamsError
from litellm.llms.base_llm.image_generation.transformation import (
BaseImageGenerationConfig,
)
@ -21,6 +22,10 @@ class AzureFoundryMAIImageGenerationConfig(BaseImageGenerationConfig):
DEFAULT_WIDTH = 1024
DEFAULT_HEIGHT = 1024
MAX_IMAGES_PER_REQUEST: Final = 1
MIN_DIMENSION_PX: Final = 768
MAX_TOTAL_PX: Final = 1_056_768
@staticmethod
def get_mai_image_generation_url(
api_base: str | None,
@ -145,16 +150,27 @@ class AzureFoundryMAIImageGenerationConfig(BaseImageGenerationConfig):
if k in supported_params:
if k == "size" and v:
self._map_size_param(v, optional_params)
self._map_size_param(v, optional_params, model)
elif k == "n" and v is not None and self._image_count(v, model) != self.MAX_IMAGES_PER_REQUEST:
if not drop_params:
raise self._unsupported(
model,
f"n={v} is not supported for model {model}. The Azure AI MAI image "
f"endpoint returns exactly {self.MAX_IMAGES_PER_REQUEST} image per "
"request and ignores any count, so a larger value would silently "
"return fewer images than requested. Send one request per image, or "
"set drop_params=True to drop n.",
)
else:
optional_params[k] = v
elif k in ("width", "height"):
optional_params[k] = v
elif not drop_params:
raise ValueError(
raise self._unsupported(
model,
f"Parameter {k} is not supported for model {model}. "
f"Supported parameters are {supported_params} and width/height. "
f"Set drop_params=True to drop unsupported parameters."
f"Set drop_params=True to drop unsupported parameters.",
)
if "width" not in optional_params:
@ -165,7 +181,19 @@ class AzureFoundryMAIImageGenerationConfig(BaseImageGenerationConfig):
optional_params.pop("size", None)
return optional_params
def _map_size_param(self, size: str, optional_params: dict) -> None:
@staticmethod
def _unsupported(model: str, message: str) -> UnsupportedParamsError:
return UnsupportedParamsError(message=message, llm_provider="azure_ai", model=model)
def _image_count(self, n: object, model: str) -> int:
if isinstance(n, int):
return n
try:
return int(str(n))
except ValueError:
raise self._unsupported(model, f"n={n!r} is not a whole number of images for model {model}.")
def _map_size_param(self, size: str, optional_params: dict, model: str) -> None:
size_mapping: Final = {
"1024x1024": (1024, 1024),
"1792x1024": (1792, 1024),
@ -176,19 +204,36 @@ class AzureFoundryMAIImageGenerationConfig(BaseImageGenerationConfig):
if size in size_mapping:
width, height = size_mapping[size]
optional_params["width"] = width
optional_params["height"] = height
elif "x" in size:
try:
width, height = map(int, size.lower().split("x"))
optional_params["width"] = width
optional_params["height"] = height
except ValueError:
raise ValueError(f"Invalid size format: '{size}'. Expected format 'WIDTHxHEIGHT' (e.g., '1024x1024').")
raise self._unsupported(
model, f"Invalid size format: '{size}'. Expected format 'WIDTHxHEIGHT' (e.g., '1024x1024')."
)
else:
raise ValueError(
raise self._unsupported(
model,
f"Unsupported size value: '{size}'. "
f"Use a known size (e.g., '1024x1024') or a custom 'WIDTHxHEIGHT' string."
f"Use a known size (e.g., '1024x1024') or a custom 'WIDTHxHEIGHT' string.",
)
self._validate_dimensions(model=model, size=size, width=width, height=height)
optional_params["width"] = width
optional_params["height"] = height
def _validate_dimensions(self, model: str, size: str, width: int, height: int) -> None:
if width < self.MIN_DIMENSION_PX or height < self.MIN_DIMENSION_PX:
raise self._unsupported(
model,
f"Unsupported size value: '{size}'. Azure AI MAI image models require width and "
f"height of at least {self.MIN_DIMENSION_PX} pixels.",
)
if width * height > self.MAX_TOTAL_PX:
raise self._unsupported(
model,
f"Unsupported size value: '{size}'. Azure AI MAI image models accept at most "
f"{self.MAX_TOTAL_PX} total pixels ({width}x{height} is {width * height}).",
)
def transform_image_generation_response(

2
litellm/utils.py
View file

@ -3412,7 +3412,7 @@ def get_optional_params_image_gen(
non_default_params=non_default_params,
optional_params=optional_params,
model=model or "",
drop_params=drop_params if drop_params is not None else False,
drop_params=litellm.drop_params is True or drop_params is True,
)
elif (
custom_llm_provider == "openai"

67
tests/test_litellm/llms/azure_ai/image_edit/test_mai_image_edit_transformation.py
View file

@ -6,6 +6,7 @@ import pytest
import litellm
from litellm.images.utils import ImageEditRequestUtils
from litellm.llms.azure_ai.image_edit import (
AzureFoundryMAIImageEditConfig,
get_azure_ai_image_edit_config,
@ -70,44 +71,48 @@ class TestAzureMAIImageEdit:
assert "/mai/v1/images/edits" in url
assert "api-version=preview" in url
def test_map_openai_params_keeps_size(self):
config = AzureFoundryMAIImageEditConfig()
optional_params = config.map_openai_params(
image_edit_optional_params={"size": "1792x1024", "n": 1},
def test_get_optional_params_image_edit_size_raises_400(self, monkeypatch):
monkeypatch.setattr(litellm, "drop_params", False)
with pytest.raises(litellm.UnsupportedParamsError, match="size") as exc_info:
ImageEditRequestUtils.get_optional_params_image_edit(
model="MAI-Image-2.5",
image_edit_provider_config=AzureFoundryMAIImageEditConfig(),
image_edit_optional_params={"size": "1024x1024", "n": 1},
)
assert exc_info.value.status_code == 400
def test_get_optional_params_image_edit_size_dropped_with_drop_params(self, monkeypatch):
monkeypatch.setattr(litellm, "drop_params", False)
optional_params = ImageEditRequestUtils.get_optional_params_image_edit(
model="MAI-Image-2.5",
image_edit_provider_config=AzureFoundryMAIImageEditConfig(),
image_edit_optional_params={"size": "1024x1024", "n": 1},
drop_params=True,
)
assert optional_params["size"] == "1792x1024"
assert "size" not in optional_params
assert optional_params["n"] == 1
assert "width" not in optional_params
assert "height" not in optional_params
def test_map_openai_params_defaults_size(self):
config = AzureFoundryMAIImageEditConfig()
optional_params = config.map_openai_params(
image_edit_optional_params={},
def test_get_optional_params_image_edit_without_size_forwards_nothing_extra(self, monkeypatch):
monkeypatch.setattr(litellm, "drop_params", False)
optional_params = ImageEditRequestUtils.get_optional_params_image_edit(
model="MAI-Image-2.5",
drop_params=True,
image_edit_provider_config=AzureFoundryMAIImageEditConfig(),
image_edit_optional_params={},
)
assert optional_params["size"] == "1024x1024"
assert optional_params == {}
def test_map_openai_params_unsupported_size_raises(self):
config = AzureFoundryMAIImageEditConfig()
with pytest.raises(ValueError, match="Unsupported size value: 'auto'"):
config.map_openai_params(
image_edit_optional_params={"size": "auto"},
model="MAI-Image-2.5",
drop_params=True,
)
def test_map_openai_params_invalid_size_format_raises(self):
config = AzureFoundryMAIImageEditConfig()
with pytest.raises(ValueError, match="Invalid size format: '1024xabc'"):
config.map_openai_params(
image_edit_optional_params={"size": "1024xabc"},
model="MAI-Image-2.5",
drop_params=True,
def test_image_edit_size_surfaces_as_400(self, monkeypatch):
monkeypatch.setattr(litellm, "drop_params", False)
with pytest.raises(litellm.BadRequestError) as exc_info:
litellm.image_edit(
model="azure_ai/MAI-Image-2.5",
image=io.BytesIO(b"fake-image-bytes"),
prompt="Turn this into a studio product shot",
size="1024x1024",
api_key="test-key",
api_base="https://my-resource.services.ai.azure.com",
)
assert exc_info.value.status_code == 400
def test_transform_image_edit_request_uses_image_field(self):
config = AzureFoundryMAIImageEditConfig()
@ -117,14 +122,14 @@ class TestAzureMAIImageEdit:
model="MAI-Image-2.5",
prompt="Turn this into a studio product shot",
image=image_bytes,
image_edit_optional_request_params={"size": "1024x1024", "n": 1},
image_edit_optional_request_params={"n": 1},
litellm_params={},
headers={},
)
assert data["model"] == "MAI-Image-2.5"
assert data["prompt"] == "Turn this into a studio product shot"
assert data["size"] == "1024x1024"
assert "size" not in data
assert data["n"] == 1
assert len(files) == 1
assert files[0][0] == "image"

173
tests/test_litellm/llms/azure_ai/image_generation/test_mai_image_generation.py
View file

@ -3,8 +3,8 @@ from unittest.mock import MagicMock
import httpx
import pytest
import litellm
from litellm.exceptions import UnsupportedParamsError
from litellm.llms.azure.azure import AzureChatCompletion
from litellm.llms.azure.image_generation import get_azure_image_generation_config
from litellm.llms.azure.image_generation.http_utils import (
@ -29,9 +29,7 @@ from litellm.utils import get_optional_params_image_gen
class TestAzureMAIImageGeneration:
def test_is_mai_model(self):
assert AzureFoundryMAIImageGenerationConfig.is_mai_model("MAI-Image-2.5")
assert AzureFoundryMAIImageGenerationConfig.is_mai_model(
"azure_ai/MAI-Image-2.5"
)
assert AzureFoundryMAIImageGenerationConfig.is_mai_model("azure_ai/MAI-Image-2.5")
assert AzureFoundryMAIImageGenerationConfig.is_mai_model("MAI-Image-2.5-Flash")
assert AzureFoundryMAIImageGenerationConfig.is_mai_model("MAI-Image-2e")
assert not AzureFoundryMAIImageGenerationConfig.is_mai_model("flux.2-pro")
@ -42,16 +40,10 @@ class TestAzureMAIImageGeneration:
api_base="https://my-resource.services.ai.azure.com",
api_version="preview",
)
assert (
url
== "https://my-resource.services.ai.azure.com/mai/v1/images/generations?api-version=preview"
)
assert url == "https://my-resource.services.ai.azure.com/mai/v1/images/generations?api-version=preview"
def test_get_mai_image_generation_url_preserves_full_path(self):
api = (
"https://my-resource.services.ai.azure.com/mai/v1/images/generations"
"?api-version=preview"
)
api = "https://my-resource.services.ai.azure.com/mai/v1/images/generations?api-version=preview"
url = AzureFoundryMAIImageGenerationConfig.get_mai_image_generation_url(
api_base=api,
api_version="preview",
@ -63,10 +55,7 @@ class TestAzureMAIImageGeneration:
api_base="https://my-resource.services.ai.azure.com/mai/v1",
api_version="preview",
)
assert (
url
== "https://my-resource.services.ai.azure.com/mai/v1/images/generations?api-version=preview"
)
assert url == "https://my-resource.services.ai.azure.com/mai/v1/images/generations?api-version=preview"
def test_get_azure_ai_image_generation_config_returns_mai(self):
config = get_azure_ai_image_generation_config("MAI-Image-2.5")
@ -104,13 +93,13 @@ class TestAzureMAIImageGeneration:
config = AzureFoundryMAIImageGenerationConfig()
optional_params = get_optional_params_image_gen(
model="MAI-Image-2.5",
size="1792x1024",
size="1024x1024",
n=1,
custom_llm_provider="azure_ai",
provider_config=config,
drop_params=True,
)
assert optional_params["width"] == 1792
assert optional_params["width"] == 1024
assert optional_params["height"] == 1024
assert "size" not in optional_params
@ -127,10 +116,7 @@ class TestAzureMAIImageGeneration:
assert "api-version=preview" in url
def test_mai_json_body_keeps_model(self):
api = (
"https://my-resource.services.ai.azure.com/mai/v1/images/generations"
"?api-version=preview"
)
api = "https://my-resource.services.ai.azure.com/mai/v1/images/generations?api-version=preview"
data = {
"model": "MAI-Image-2.5",
"prompt": "A photograph of a red fox",
@ -176,7 +162,7 @@ class TestAzureMAIImageGeneration:
def test_map_openai_params_unsupported_size_raises(self):
config = AzureFoundryMAIImageGenerationConfig()
with pytest.raises(ValueError, match="Unsupported size value: 'auto'"):
with pytest.raises(UnsupportedParamsError, match="Unsupported size value: 'auto'"):
config.map_openai_params(
non_default_params={"size": "auto"},
optional_params={},
@ -186,7 +172,7 @@ class TestAzureMAIImageGeneration:
def test_map_openai_params_invalid_custom_size_raises(self):
config = AzureFoundryMAIImageGenerationConfig()
with pytest.raises(ValueError, match="Invalid size format: '1024xabc'"):
with pytest.raises(UnsupportedParamsError, match="Invalid size format: '1024xabc'"):
config.map_openai_params(
non_default_params={"size": "1024xabc"},
optional_params={},
@ -194,9 +180,138 @@ class TestAzureMAIImageGeneration:
drop_params=True,
)
@pytest.mark.parametrize("size", ["512x512", "256x256", "700x1400"])
def test_map_openai_params_size_below_minimum_dimension_raises(self, size):
config = AzureFoundryMAIImageGenerationConfig()
with pytest.raises(UnsupportedParamsError, match="at least 768 pixels"):
config.map_openai_params(
non_default_params={"size": size},
optional_params={},
model="MAI-Image-2.5",
drop_params=True,
)
@pytest.mark.parametrize("size", ["1792x1024", "1024x1792"])
def test_map_openai_params_size_over_total_pixel_budget_raises(self, size):
config = AzureFoundryMAIImageGenerationConfig()
with pytest.raises(UnsupportedParamsError, match="at most 1056768 total pixels"):
config.map_openai_params(
non_default_params={"size": size},
optional_params={},
model="MAI-Image-2.5",
drop_params=True,
)
@pytest.mark.parametrize("size", ["1032x1024", "1376x768"])
def test_map_openai_params_size_at_live_pixel_cap_passes_through(self, size):
config = AzureFoundryMAIImageGenerationConfig()
optional_params = config.map_openai_params(
non_default_params={"size": size},
optional_params={},
model="MAI-Image-2.5",
drop_params=False,
)
assert optional_params["width"] * optional_params["height"] == 1_056_768
def test_map_openai_params_size_one_pixel_over_live_cap_raises(self):
config = AzureFoundryMAIImageGenerationConfig()
with pytest.raises(UnsupportedParamsError, match="at most 1056768 total pixels"):
config.map_openai_params(
non_default_params={"size": "1033x1024"},
optional_params={},
model="MAI-Image-2.5",
drop_params=False,
)
def test_map_openai_params_explicit_width_height_not_range_checked(self):
config = AzureFoundryMAIImageGenerationConfig()
optional_params = config.map_openai_params(
non_default_params={"width": 1792, "height": 1024},
optional_params={},
model="MAI-Image-2.5",
drop_params=True,
)
assert optional_params["width"] == 1792
assert optional_params["height"] == 1024
@pytest.mark.parametrize("n", [2, 4, "2", 0, -1])
def test_map_openai_params_n_other_than_one_raises(self, n):
config = AzureFoundryMAIImageGenerationConfig()
with pytest.raises(UnsupportedParamsError, match="returns exactly 1 image per request"):
config.map_openai_params(
non_default_params={"n": n},
optional_params={},
model="MAI-Image-2.5",
drop_params=False,
)
def test_map_openai_params_non_numeric_n_raises_400(self):
config = AzureFoundryMAIImageGenerationConfig()
with pytest.raises(UnsupportedParamsError, match="not a whole number of images") as exc_info:
config.map_openai_params(
non_default_params={"n": "abc"},
optional_params={},
model="MAI-Image-2.5",
drop_params=False,
)
assert exc_info.value.status_code == 400
def test_get_optional_params_image_gen_global_drop_params_drops_multi_image_n(self, monkeypatch):
monkeypatch.setattr(litellm, "drop_params", True)
optional_params = get_optional_params_image_gen(
model="MAI-Image-2.5",
n=4,
custom_llm_provider="azure_ai",
provider_config=AzureFoundryMAIImageGenerationConfig(),
)
assert "n" not in optional_params
assert optional_params["width"] == 1024
def test_get_optional_params_image_gen_without_any_drop_params_still_raises(self, monkeypatch):
monkeypatch.setattr(litellm, "drop_params", False)
with pytest.raises(UnsupportedParamsError, match="returns exactly 1 image per request"):
get_optional_params_image_gen(
model="MAI-Image-2.5",
n=4,
custom_llm_provider="azure_ai",
provider_config=AzureFoundryMAIImageGenerationConfig(),
)
def test_map_openai_params_multi_image_n_dropped_with_drop_params(self):
config = AzureFoundryMAIImageGenerationConfig()
optional_params = config.map_openai_params(
non_default_params={"n": 4},
optional_params={},
model="MAI-Image-2.5",
drop_params=True,
)
assert "n" not in optional_params
def test_map_openai_params_single_image_n_still_passes_through(self):
config = AzureFoundryMAIImageGenerationConfig()
optional_params = config.map_openai_params(
non_default_params={"n": 1},
optional_params={},
model="MAI-Image-2.5",
drop_params=False,
)
assert optional_params["n"] == 1
@pytest.mark.parametrize("params", [{"n": 2}, {"n": "abc"}, {"size": "512x512"}, {"size": "1792x1024"}])
def test_image_generation_rejected_params_surface_as_400(self, params):
with pytest.raises(litellm.BadRequestError) as exc_info:
litellm.image_generation(
model="azure_ai/MAI-Image-2.5",
prompt="A photograph of a red fox",
api_key="test-key",
api_base="https://my-resource.services.ai.azure.com",
**params,
)
assert exc_info.value.status_code == 400
def test_map_openai_params_unsupported_param_raises(self):
config = AzureFoundryMAIImageGenerationConfig()
with pytest.raises(ValueError, match="Parameter quality is not supported"):
with pytest.raises(UnsupportedParamsError, match="Parameter quality is not supported"):
config.map_openai_params(
non_default_params={"quality": "hd"},
optional_params={},
@ -343,16 +458,12 @@ class TestAzureMAIImageGeneration:
litellm.model_cost = litellm.get_model_cost_map(url="")
model = "azure_ai/MAI-Image-2.5"
model_info = litellm.get_model_info(model=model, custom_llm_provider="azure_ai")
image_response = ImageResponse(
data=[ImageObject(b64_json="img1"), ImageObject(b64_json="img2")]
)
image_response = ImageResponse(data=[ImageObject(b64_json="img1"), ImageObject(b64_json="img2")])
cost = azure_ai_image_cost_calculator(
model=model,
image_response=image_response,
)
assert (
cost == len(image_response.data or []) * model_info["output_cost_per_image"]
)
assert cost == len(image_response.data or []) * model_info["output_cost_per_image"]
assert cost > 0