fix(utils.py): fix vertex ai optional param handling

don't pass max retries to unsupported route

Fixes #8254

litellm/llms/vertex_ai/vertex_ai_partner_models/llama3/transformation.py

@@ -2,9 +2,10 @@
 from typing import Optional
 
 import litellm
+from litellm.llms.openai.chat.gpt_transformation import OpenAIGPTConfig
 
 
-class VertexAILlama3Config:
+class VertexAILlama3Config(OpenAIGPTConfig):
     """
     Reference:https://cloud.google.com/vertex-ai/generative-ai/docs/partner-models/llama#streaming
 
@@ -46,8 +47,13 @@ def get_config(cls):
             and v is not None
         }
 
-    def get_supported_openai_params(self):
-        return litellm.OpenAIConfig().get_supported_openai_params(model="gpt-3.5-turbo")
+    def get_supported_openai_params(self, model: str):
+        supported_params = super().get_supported_openai_params(model=model)
+        try:
+            supported_params.remove("max_retries")
+        except KeyError:
+            pass
+        return supported_params
 
     def map_openai_params(
         self,
@@ -60,7 +66,7 @@ def map_openai_params(
             non_default_params["max_tokens"] = non_default_params.pop(
                 "max_completion_tokens"
             )
-        return litellm.OpenAIConfig().map_openai_params(
+        return super().map_openai_params(
             non_default_params=non_default_params,
             optional_params=optional_params,
             model=model,

litellm/utils.py

@@ -3166,51 +3166,56 @@ def _check_valid_arg(supported_params: List[str]):
                 else False
             ),
         )
-    elif custom_llm_provider == "vertex_ai" and model in litellm.vertex_llama3_models:
-        optional_params = litellm.VertexAILlama3Config().map_openai_params(
-            non_default_params=non_default_params,
-            optional_params=optional_params,
-            model=model,
-            drop_params=(
-                drop_params
-                if drop_params is not None and isinstance(drop_params, bool)
-                else False
-            ),
-        )
-    elif custom_llm_provider == "vertex_ai" and model in litellm.vertex_mistral_models:
-        if "codestral" in model:
-            optional_params = litellm.CodestralTextCompletionConfig().map_openai_params(
-                model=model,
+    elif custom_llm_provider == "vertex_ai":
+
+        if model in litellm.vertex_mistral_models:
+            if "codestral" in model:
+                optional_params = (
+                    litellm.CodestralTextCompletionConfig().map_openai_params(
+                        model=model,
+                        non_default_params=non_default_params,
+                        optional_params=optional_params,
+                        drop_params=(
+                            drop_params
+                            if drop_params is not None and isinstance(drop_params, bool)
+                            else False
+                        ),
+                    )
+                )
+            else:
+                optional_params = litellm.MistralConfig().map_openai_params(
+                    model=model,
+                    non_default_params=non_default_params,
+                    optional_params=optional_params,
+                    drop_params=(
+                        drop_params
+                        if drop_params is not None and isinstance(drop_params, bool)
+                        else False
+                    ),
+                )
+        elif model in litellm.vertex_ai_ai21_models:
+            optional_params = litellm.VertexAIAi21Config().map_openai_params(
                 non_default_params=non_default_params,
                 optional_params=optional_params,
+                model=model,
                 drop_params=(
                     drop_params
                     if drop_params is not None and isinstance(drop_params, bool)
                     else False
                 ),
             )
-        else:
-            optional_params = litellm.MistralConfig().map_openai_params(
-                model=model,
+        else:  # use generic openai-like param mapping
+            optional_params = litellm.VertexAILlama3Config().map_openai_params(
                 non_default_params=non_default_params,
                 optional_params=optional_params,
+                model=model,
                 drop_params=(
                     drop_params
                     if drop_params is not None and isinstance(drop_params, bool)
                     else False
                 ),
             )
-    elif custom_llm_provider == "vertex_ai" and model in litellm.vertex_ai_ai21_models:
-        optional_params = litellm.VertexAIAi21Config().map_openai_params(
-            non_default_params=non_default_params,
-            optional_params=optional_params,
-            model=model,
-            drop_params=(
-                drop_params
-                if drop_params is not None and isinstance(drop_params, bool)
-                else False
-            ),
-        )
+
     elif custom_llm_provider == "sagemaker":
         # temperature, top_p, n, stream, stop, max_tokens, n, presence_penalty default to None
         optional_params = litellm.SagemakerConfig().map_openai_params(

tests/llm_translation/test_optional_params.py

@@ -1067,3 +1067,14 @@ def test_gemini_frequency_penalty():
         model="gemini-1.5-flash", custom_llm_provider="gemini", frequency_penalty=0.5
     )
     assert optional_params["frequency_penalty"] == 0.5
+
+
+def test_vertex_ai_ft_llama():
+    optional_params = get_optional_params(
+        model="1984786713414729728",
+        custom_llm_provider="vertex_ai",
+        frequency_penalty=0.5,
+        max_retries=10,
+    )
+    assert optional_params["frequency_penalty"] == 0.5
+    assert "max_retries" not in optional_params