use helper for image gen tests (#7343)

litellm/cost_calculator.py

@@ -473,8 +473,8 @@ def completion_cost(  # noqa: PLR0915
     region_name=None,  # used for bedrock pricing
     ### IMAGE GEN ###
     size: Optional[str] = None,
-    quality=None,
-    n=None,  # number of images
+    quality: Optional[str] = None,
+    n: Optional[int] = None,  # number of images
     ### CUSTOM PRICING ###
     custom_cost_per_token: Optional[CostPerToken] = None,
     custom_cost_per_second: Optional[float] = None,
@@ -640,41 +640,14 @@ def completion_cost(  # noqa: PLR0915
                 raise TypeError(
                     "completion_response must be of type ImageResponse for bedrock image cost calculation"
                 )
-            if size is None:
-                size = "1024-x-1024"  # openai default
-            # fix size to match naming convention
-            if "x" in size and "-x-" not in size:
-                size = size.replace("x", "-x-")
-            image_gen_model_name = f"{size}/{model}"
-            image_gen_model_name_with_quality = image_gen_model_name
-            if quality is not None:
-                image_gen_model_name_with_quality = f"{quality}/{image_gen_model_name}"
-            size_parts = size.split("-x-")
-            height = int(size_parts[0])  # if it's 1024-x-1024 vs. 1024x1024
-            width = int(size_parts[1])
-            verbose_logger.debug(f"image_gen_model_name: {image_gen_model_name}")
-            verbose_logger.debug(
-                f"image_gen_model_name_with_quality: {image_gen_model_name_with_quality}"
-            )
-            if image_gen_model_name in litellm.model_cost:
-                return (
-                    litellm.model_cost[image_gen_model_name]["input_cost_per_pixel"]
-                    * height
-                    * width
-                    * n
-                )
-            elif image_gen_model_name_with_quality in litellm.model_cost:
-                return (
-                    litellm.model_cost[image_gen_model_name_with_quality][
-                        "input_cost_per_pixel"
-                    ]
-                    * height
-                    * width
-                    * n
-                )
             else:
-                raise Exception(
-                    f"Model={image_gen_model_name} not found in completion cost model map"
+                return default_image_cost_calculator(
+                    model=model,
+                    quality=quality,
+                    custom_llm_provider=custom_llm_provider,
+                    n=n,
+                    size=size,
+                    optional_params=optional_params,
                 )
         elif (
             call_type == CallTypes.speech.value or call_type == CallTypes.aspeech.value
@@ -869,3 +842,65 @@ def transcription_cost(
     return openai_cost_per_second(
         model=model, custom_llm_provider=custom_llm_provider, duration=duration
     )
+
+
+def default_image_cost_calculator(
+    model: str,
+    custom_llm_provider: Optional[str] = None,
+    quality: Optional[str] = None,
+    n: Optional[int] = 1,  # Default to 1 image
+    size: Optional[str] = "1024-x-1024",  # OpenAI default
+    optional_params: Optional[dict] = None,
+) -> float:
+    """
+    Default image cost calculator for image generation
+
+    Args:
+        model (str): Model name
+        image_response (ImageResponse): Response from image generation
+        quality (Optional[str]): Image quality setting
+        n (Optional[int]): Number of images generated
+        size (Optional[str]): Image size (e.g. "1024x1024" or "1024-x-1024")
+
+    Returns:
+        float: Cost in USD for the image generation
+
+    Raises:
+        Exception: If model pricing not found in cost map
+    """
+    # Standardize size format to use "-x-"
+    size_str: str = size or "1024-x-1024"
+    size_str = (
+        size_str.replace("x", "-x-")
+        if "x" in size_str and "-x-" not in size_str
+        else size_str
+    )
+
+    # Parse dimensions
+    height, width = map(int, size_str.split("-x-"))
+
+    # Build model names for cost lookup
+    base_model_name = f"{size_str}/{model}"
+    if custom_llm_provider and model.startswith(custom_llm_provider):
+        base_model_name = (
+            f"{custom_llm_provider}/{size_str}/{model.replace(custom_llm_provider, '')}"
+        )
+    model_name_with_quality = (
+        f"{quality}/{base_model_name}" if quality else base_model_name
+    )
+
+    verbose_logger.debug(
+        f"Looking up cost for models: {model_name_with_quality}, {base_model_name}"
+    )
+
+    # Try model with quality first, fall back to base model name
+    if model_name_with_quality in litellm.model_cost:
+        cost_info = litellm.model_cost[model_name_with_quality]
+    elif base_model_name in litellm.model_cost:
+        cost_info = litellm.model_cost[base_model_name]
+    else:
+        raise Exception(
+            f"Model not found in cost map. Tried {model_name_with_quality} and {base_model_name}"
+        )
+
+    return cost_info["input_cost_per_pixel"] * height * width * n

tests/image_gen_tests/test_image_generation.py

@@ -6,6 +6,11 @@ import os
 import sys
 import traceback
 
+
+sys.path.insert(
+    0, os.path.abspath("../..")
+)  # Adds the parent directory to the system path
+
 from dotenv import load_dotenv
 from openai.types.image import Image
 from litellm.caching import InMemoryCache
@@ -14,10 +19,6 @@ logging.basicConfig(level=logging.DEBUG)
 load_dotenv()
 import asyncio
 import os
-
-sys.path.insert(
-    0, os.path.abspath("../..")
-)  # Adds the parent directory to the system path
 import pytest
 
 import litellm
@@ -142,7 +143,7 @@ class TestAzureOpenAIDalle3(BaseImageGenTest):
             "api_version": "2023-09-01-preview",
             "metadata": {
                 "model_info": {
-                    "base_model": "dall-e-3",
+                    "base_model": "azure/dall-e-3",
                 }
             },
         }
@@ -158,8 +159,15 @@ def test_image_generation_azure_dall_e_3():
             api_version="2023-12-01-preview",
             api_base=os.getenv("AZURE_SWEDEN_API_BASE"),
             api_key=os.getenv("AZURE_SWEDEN_API_KEY"),
+            metadata={
+                "model_info": {
+                    "base_model": "azure/dall-e-3",
+                }
+            },
         )
         print(f"response: {response}")
+
+        print("response", response._hidden_params)
         assert len(response.data) > 0
     except litellm.InternalServerError as e:
         pass