chore: update the vertexai inference impl to use openai-python for openai-compat functions

llama_stack/providers/registry/inference.py

@@ -218,7 +218,7 @@ def available_providers() -> list[ProviderSpec]:
             api=Api.inference,
             adapter=AdapterSpec(
                 adapter_type="vertexai",
-                pip_packages=["litellm", "google-cloud-aiplatform"],
+                pip_packages=["litellm", "google-cloud-aiplatform", "openai"],
                 module="llama_stack.providers.remote.inference.vertexai",
                 config_class="llama_stack.providers.remote.inference.vertexai.VertexAIConfig",
                 provider_data_validator="llama_stack.providers.remote.inference.vertexai.config.VertexAIProviderDataValidator",

llama_stack/providers/remote/inference/vertexai/vertexai.py

@@ -6,16 +6,20 @@
 
 from typing import Any
 
+import google.auth.transport.requests
+from google.auth import default
+
 from llama_stack.apis.inference import ChatCompletionRequest
 from llama_stack.providers.utils.inference.litellm_openai_mixin import (
     LiteLLMOpenAIMixin,
 )
+from llama_stack.providers.utils.inference.openai_mixin import OpenAIMixin
 
 from .config import VertexAIConfig
 from .models import MODEL_ENTRIES
 
 
-class VertexAIInferenceAdapter(LiteLLMOpenAIMixin):
+class VertexAIInferenceAdapter(OpenAIMixin, LiteLLMOpenAIMixin):
     def __init__(self, config: VertexAIConfig) -> None:
         LiteLLMOpenAIMixin.__init__(
             self,
@@ -27,9 +31,30 @@ def __init__(self, config: VertexAIConfig) -> None:
         self.config = config
 
     def get_api_key(self) -> str:
-        # Vertex AI doesn't use API keys, it uses Application Default Credentials
-        # Return empty string to let litellm handle authentication via ADC
-        return ""
+        """
+        Get an access token for Vertex AI using Application Default Credentials.
+
+        Vertex AI uses ADC instead of API keys. This method obtains an access token
+        from the default credentials and returns it for use with the OpenAI-compatible client.
+        """
+        try:
+            # Get default credentials - will read from GOOGLE_APPLICATION_CREDENTIALS
+            credentials, _ = default(scopes=["https://www.googleapis.com/auth/cloud-platform"])
+            credentials.refresh(google.auth.transport.requests.Request())
+            return credentials.token
+        except Exception:
+            # If we can't get credentials, return empty string to let LiteLLM handle it
+            # This allows the LiteLLM mixin to work with ADC directly
+            return ""
+
+    def get_base_url(self) -> str:
+        """
+        Get the Vertex AI OpenAI-compatible API base URL.
+
+        Returns the Vertex AI OpenAI-compatible endpoint URL.
+        Source: https://cloud.google.com/vertex-ai/generative-ai/docs/start/openai
+        """
+        return f"https://{self.config.location}-aiplatform.googleapis.com/v1/projects/{self.config.project}/locations/{self.config.location}/endpoints/openapi"
 
     async def _get_params(self, request: ChatCompletionRequest) -> dict[str, Any]:
         # Get base parameters from parent

tests/integration/inference/test_openai_completion.py

@@ -76,6 +76,9 @@ def skip_if_doesnt_support_n(client_with_models, model_id):
         "remote::gemini",
         # https://docs.anthropic.com/en/api/openai-sdk#simple-fields
         "remote::anthropic",
+        "remote::vertexai",
+        #  Error code: 400 - [{'error': {'code': 400, 'message': 'Unable to submit request because candidateCount must be 1 but
+        #  the entered value was 2. Update the candidateCount value and try again.', 'status': 'INVALID_ARGUMENT'}
     ):
         pytest.skip(f"Model {model_id} hosted by {provider.provider_type} doesn't support n param.")