fix: enforce allowed_models during inference requests (backport #4197) (#4228)

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 <hr>This is an automatic backport of pull request #4197
done by [Mergify](https://mergify.com).

Signed-off-by: Charlie Doern <cdoern@redhat.com>
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>

llama_stack/providers/utils/inference/openai_mixin.py

@@ -188,6 +188,19 @@ 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.
@@ -234,8 +247,11 @@ 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,
@@ -267,6 +283,9 @@ 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:
@@ -288,7 +307,7 @@ 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,
@@ -326,9 +345,13 @@ class OpenAIMixin(NeedsRequestProviderData, ABC, BaseModel):
         """
         Direct OpenAI embeddings API call.
         """
-        # Prepare request parameters
+        provider_model_id = await self._get_provider_model_id(params.model)
-        request_params = {
+        self._validate_model_allowed(provider_model_id)
-            "model": await self._get_provider_model_id(params.model),
+
+        # 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": provider_model_id,
             "input": params.input,
             "encoding_format": params.encoding_format if params.encoding_format is not None else NOT_GIVEN,
             "dimensions": params.dimensions if params.dimensions is not None else NOT_GIVEN,

tests/unit/providers/utils/inference/test_openai_mixin.py

@@ -12,7 +12,13 @@ from unittest.mock import AsyncMock, MagicMock, Mock, PropertyMock, patch
 import pytest
 from pydantic import BaseModel, Field
 
-from llama_stack.apis.inference import Model, OpenAIChatCompletionRequestWithExtraBody, OpenAIUserMessageParam
+from llama_stack.apis.inference import (
+    Model,
+    OpenAIChatCompletionRequestWithExtraBody,
+    OpenAICompletionRequestWithExtraBody,
+    OpenAIEmbeddingsRequestWithExtraBody,
+    OpenAIUserMessageParam,
+)
 from llama_stack.apis.models import ModelType
 from llama_stack.core.request_headers import request_provider_data_context
 from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
@@ -743,3 +749,96 @@ class TestOpenAIMixinProviderDataApiKey:
         error_message = str(exc_info.value)
         assert "test_api_key" in error_message
         assert "x-llamastack-provider-data" in error_message
+
+
+class TestOpenAIMixinAllowedModelsInference:
+    """Test cases for allowed_models enforcement during inference requests"""
+
+    async def test_inference_with_allowed_models(self, mixin, mock_client_context):
+        """Test that all inference methods succeed with allowed models"""
+        mixin.config.allowed_models = ["gpt-4", "text-davinci-003", "text-embedding-ada-002"]
+
+        mock_client = MagicMock()
+        mock_client.chat.completions.create = AsyncMock(return_value=MagicMock())
+        mock_client.completions.create = AsyncMock(return_value=MagicMock())
+        mock_embedding_response = MagicMock()
+        mock_embedding_response.data = [MagicMock(embedding=[0.1, 0.2, 0.3])]
+        mock_embedding_response.usage = MagicMock(prompt_tokens=5, total_tokens=5)
+        mock_client.embeddings.create = AsyncMock(return_value=mock_embedding_response)
+
+        with mock_client_context(mixin, mock_client):
+            # Test chat completion
+            await mixin.openai_chat_completion(
+                OpenAIChatCompletionRequestWithExtraBody(
+                    model="gpt-4", messages=[OpenAIUserMessageParam(role="user", content="Hello")]
+                )
+            )
+            mock_client.chat.completions.create.assert_called_once()
+
+            # Test completion
+            await mixin.openai_completion(
+                OpenAICompletionRequestWithExtraBody(model="text-davinci-003", prompt="Hello")
+            )
+            mock_client.completions.create.assert_called_once()
+
+            # Test embeddings
+            await mixin.openai_embeddings(
+                OpenAIEmbeddingsRequestWithExtraBody(model="text-embedding-ada-002", input="test text")
+            )
+            mock_client.embeddings.create.assert_called_once()
+
+    async def test_inference_with_disallowed_models(self, mixin, mock_client_context):
+        """Test that all inference methods fail with disallowed models"""
+        mixin.config.allowed_models = ["gpt-4"]
+
+        mock_client = MagicMock()
+
+        with mock_client_context(mixin, mock_client):
+            # Test chat completion with disallowed model
+            with pytest.raises(ValueError, match="Model 'gpt-4-turbo' is not in the allowed models list"):
+                await mixin.openai_chat_completion(
+                    OpenAIChatCompletionRequestWithExtraBody(
+                        model="gpt-4-turbo", messages=[OpenAIUserMessageParam(role="user", content="Hello")]
+                    )
+                )
+
+            # Test completion with disallowed model
+            with pytest.raises(ValueError, match="Model 'text-davinci-002' is not in the allowed models list"):
+                await mixin.openai_completion(
+                    OpenAICompletionRequestWithExtraBody(model="text-davinci-002", prompt="Hello")
+                )
+
+            # Test embeddings with disallowed model
+            with pytest.raises(ValueError, match="Model 'text-embedding-3-large' is not in the allowed models list"):
+                await mixin.openai_embeddings(
+                    OpenAIEmbeddingsRequestWithExtraBody(model="text-embedding-3-large", input="test text")
+                )
+
+            mock_client.chat.completions.create.assert_not_called()
+            mock_client.completions.create.assert_not_called()
+            mock_client.embeddings.create.assert_not_called()
+
+    async def test_inference_with_no_restrictions(self, mixin, mock_client_context):
+        """Test that inference succeeds when allowed_models is None or empty list blocks all"""
+        # Test with None (no restrictions)
+        assert mixin.config.allowed_models is None
+        mock_client = MagicMock()
+        mock_client.chat.completions.create = AsyncMock(return_value=MagicMock())
+
+        with mock_client_context(mixin, mock_client):
+            await mixin.openai_chat_completion(
+                OpenAIChatCompletionRequestWithExtraBody(
+                    model="any-model", messages=[OpenAIUserMessageParam(role="user", content="Hello")]
+                )
+            )
+            mock_client.chat.completions.create.assert_called_once()
+
+        # Test with empty list (blocks all models)
+        mixin.config.allowed_models = []
+        with mock_client_context(mixin, mock_client):
+            with pytest.raises(ValueError, match="Model 'gpt-4' is not in the allowed models list"):
+                await mixin.openai_chat_completion(
+                    OpenAIChatCompletionRequestWithExtraBody(
+                        model="gpt-4", messages=[OpenAIUserMessageParam(role="user", content="Hello")]
+                    )
+                )