_is_model_gemini_gemini_spec_model

litellm/llms/vertex_ai/common_utils.py

@@ -3,6 +3,7 @@ from typing import Dict, List, Literal, Optional, Tuple, Union
 
 import httpx
 
+import litellm
 from litellm import supports_response_schema, supports_system_messages, verbose_logger
 from litellm.llms.base_llm.chat.transformation import BaseLLMException
 from litellm.types.llms.vertex_ai import PartType
@@ -28,6 +29,10 @@ def get_supports_system_message(
         supports_system_message = supports_system_messages(
             model=model, custom_llm_provider=_custom_llm_provider
         )
+
+        # Vertex Models called in the `/gemini` request/response format also support system messages
+        if litellm.VertexGeminiConfig._is_model_gemini_gemini_spec_model(model):
+            supports_system_message = True
     except Exception as e:
         verbose_logger.warning(
             "Unable to identify if system message supported. Defaulting to 'False'. Received error message - {}\nAdd it here - https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json".format(

litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py

@@ -207,7 +207,7 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
             "extra_headers",
             "seed",
             "logprobs",
-            "top_logprobs" # Added this to list of supported openAI params
+            "top_logprobs",  # Added this to list of supported openAI params
         ]
 
     def map_tool_choice_values(
@@ -419,6 +419,17 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
             "europe-west9",
         ]
 
+    @staticmethod
+    def _is_model_gemini_gemini_spec_model(model: Optional[str]) -> bool:
+        """
+        Returns true if user is trying to call custom model in `/gemini` request/response format
+        """
+        if model is None:
+            return False
+        if "gemini/" in model:
+            return True
+        return False
+
     def get_flagged_finish_reasons(self) -> Dict[str, str]:
         """
         Return Dictionary of finish reasons which indicate response was flagged

litellm/main.py

@@ -1097,10 +1097,7 @@ def completion(  # type: ignore # noqa: PLR0915
             logit_bias=logit_bias,
             user=user,
             # params to identify the model
-            model=LitellmCoreRequestUtils.select_model_for_request_transformation(
             model=model,
-                base_model=base_model,
-            ),
             custom_llm_provider=custom_llm_provider,
             response_format=response_format,
             seed=seed,

tests/local_testing/test_amazing_vertex_completion.py

@@ -3380,8 +3380,7 @@ def test_gemini_fine_tuned_model_request_consistency():
     with patch.object(client, "post", new=MagicMock()) as mock_post_1:
         try:
             response_1 = completion(
-                model="vertex_ai/ft-uuid",
-                base_model="vertex_ai/gemini-2.0-flash-001",
+                model="vertex_ai/gemini/ft-uuid",
                 messages=messages,
                 tools=tools,
                 tool_choice="auto",