fix: enforce allowed_models during inference requests (#4197)

The `allowed_models` configuration was only being applied when listing
models via the `/v1/models` endpoint, but the actual inference requests
weren't checking this restriction. This meant users could directly
request any model the provider supports by specifying it in their
inference call, completely bypassing the intended cost controls.

The fix adds validation to all three inference methods (chat
completions, completions, and embeddings) that checks the requested
model against the allowed_models list before making the provider API
call.

### Test plan

Added unit tests

src/llama_stack/providers/utils/inference/openai_mixin.py

@@ -213,6 +213,19 @@ class OpenAIMixin(NeedsRequestProviderData, ABC, BaseModel):
 
         return api_key
 
+    def _validate_model_allowed(self, provider_model_id: str) -> None:
+        """
+        Validate that the model is in the allowed_models list if configured.
+
+        :param provider_model_id: The provider-specific model ID to validate
+        :raises ValueError: If the model is not in the allowed_models list
+        """
+        if self.config.allowed_models is not None and provider_model_id not in self.config.allowed_models:
+            raise ValueError(
+                f"Model '{provider_model_id}' is not in the allowed models list. "
+                f"Allowed models: {self.config.allowed_models}"
+            )
+
     async def _get_provider_model_id(self, model: str) -> str:
         """
         Get the provider-specific model ID from the model store.
@@ -259,8 +272,11 @@ class OpenAIMixin(NeedsRequestProviderData, ABC, BaseModel):
         Direct OpenAI completion API call.
         """
         # TODO: fix openai_completion to return type compatible with OpenAI's API response
+        provider_model_id = await self._get_provider_model_id(params.model)
+        self._validate_model_allowed(provider_model_id)
+
         completion_kwargs = await prepare_openai_completion_params(
-            model=await self._get_provider_model_id(params.model),
+            model=provider_model_id,
             prompt=params.prompt,
             best_of=params.best_of,
             echo=params.echo,
@@ -292,6 +308,9 @@ class OpenAIMixin(NeedsRequestProviderData, ABC, BaseModel):
         """
         Direct OpenAI chat completion API call.
         """
+        provider_model_id = await self._get_provider_model_id(params.model)
+        self._validate_model_allowed(provider_model_id)
+
         messages = params.messages
 
         if self.download_images:
@@ -313,7 +332,7 @@ class OpenAIMixin(NeedsRequestProviderData, ABC, BaseModel):
             messages = [await _localize_image_url(m) for m in messages]
 
         request_params = await prepare_openai_completion_params(
-            model=await self._get_provider_model_id(params.model),
+            model=provider_model_id,
             messages=messages,
             frequency_penalty=params.frequency_penalty,
             function_call=params.function_call,
@@ -351,10 +370,13 @@ class OpenAIMixin(NeedsRequestProviderData, ABC, BaseModel):
         """
         Direct OpenAI embeddings API call.
         """
+        provider_model_id = await self._get_provider_model_id(params.model)
+        self._validate_model_allowed(provider_model_id)
+
         # Build request params conditionally to avoid NotGiven/Omit type mismatch
         # The OpenAI SDK uses Omit in signatures but NOT_GIVEN has type NotGiven
         request_params: dict[str, Any] = {
-            "model": await self._get_provider_model_id(params.model),
+            "model": provider_model_id,
             "input": params.input,
         }
         if params.encoding_format is not None: