fix: ci test

gemini 2.5 depricated

tests/llm_translation/test_gemini.py

@@ -293,7 +293,7 @@ def test_gemini_image_generation():
 @pytest.mark.parametrize(
     "model_name",
     [
-        "gemini/gemini-2.5-flash-image-preview",
+        "gemini/gemini-2.5-flash-image",
         "gemini/gemini-2.0-flash-preview-image-generation",
         "gemini/gemini-3-pro-image-preview",
     ],
@@ -733,7 +733,7 @@ async def test_gemini_image_generation_async():
                 "content": "Generate an image of a banana wearing a costume that says LiteLLM",
             }
         ],
-        model="gemini/gemini-2.5-flash-image-preview",
+        model="gemini/gemini-2.5-flash-image",
     )
 
     CONTENT = response.choices[0].message.content
@@ -762,7 +762,7 @@ async def test_gemini_image_generation_async_stream():
                 "content": "Generate an image of a banana wearing a costume that says LiteLLM",
             }
         ],
-        model="gemini/gemini-2.5-flash-image-preview",
+        model="gemini/gemini-2.5-flash-image",
         stream=True,
     )
 

tests/llm_translation/test_gemini_image_usage.py

@@ -13,7 +13,7 @@ from litellm.types.utils import ImageResponse, ImageObject, ImageUsage
 @pytest.mark.parametrize(
     "model_name",
     [
-        "gemini/gemini-2.5-flash-image-preview",
+        "gemini/gemini-2.5-flash-image",
         "gemini/gemini-2.0-flash-preview-image-generation",
         "gemini/gemini-3-pro-image-preview",
     ],
@@ -211,4 +211,3 @@ def test_gemini_imagen_models_no_usage_extraction():
         
         # For Imagen models, we don't extract usage from the predictions format
         # This test just ensures we don't crash
-

tests/llm_translation/test_openrouter.py

@@ -22,7 +22,7 @@ def test_completion_openrouter_reasoning_content():
 def test_completion_openrouter_image_generation():
     litellm._turn_on_debug()
     resp = litellm.completion(
-        model="openrouter/google/gemini-2.5-flash-image-preview",
+        model="openrouter/google/gemini-2.5-flash-image",
         messages=[{"role": "user", "content": "Generate an image of a cat"}],
         modalities=["image", "text"],
     )