fix(azure_ai): preserve fallback for empty FLUX.2 image responses

litellm/llms/azure_ai/image_generation/cost_calculator.py

@@ -50,13 +50,15 @@ def record_megapixel_usage(response: object, response_body: bytes | Mapping[str,
 
 
 def _megapixel_cost(model_info: ModelInfo, image_response: ImageResponse) -> float | None:
+    images: Final = len(image_response.data or ())
+    if not images:
+        return None
     try:
         prices: Final = _MegapixelPrices.model_validate(model_info)
         usage: Final = _MegapixelUsage.model_validate(image_response.hidden_params.get(_MEGAPIXEL_USAGE_HIDDEN_PARAM))
     except ValidationError:
         return None
     first_rate: Final = prices.output_cost_per_first_megapixel
-    images: Final = max(len(image_response.data or ()), 1)
     output_mp_per_image: Final = usage.output_mp / images
     return images * (
         (prices.output_cost_per_megapixel if first_rate is None else first_rate)

tests/unit/llms/azure_ai/image_generation/test_azure_ai_flux2_image_generation.py

@@ -334,6 +334,20 @@ def test_flux2_pro_generation_bills_first_megapixel_per_returned_image(
     )
 
 
+@respx.mock
+def test_flux2_pro_generation_without_returned_images_has_no_cost() -> None:
+    respx.post(url__regex=_flux2_route("flux-2-pro")).mock(
+        return_value=httpx.Response(200, json=_metered_body(3.0, 1.5, num_images=0))
+    )
+
+    response: Final = litellm.image_generation(
+        model="azure_ai/flux.2-pro", prompt="A red fox", n=4, api_base=FOUNDRY_BASE, api_key="test-key"
+    )
+
+    assert response.data == []
+    assert response._hidden_params["response_cost"] == 0.0
+
+
 @pytest.mark.asyncio
 async def test_async_flux2_pro_generation_bills_the_reported_megapixels(
     respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch