feat: allow dynamic model registration for nvidia inference provider

implements query_available_models on NVIDIAInferenceAdapter

llama_stack/providers/remote/inference/nvidia/nvidia.py

@@ -41,11 +41,7 @@ from llama_stack.apis.inference import (
     ToolChoice,
     ToolConfig,
 )
-from llama_stack.apis.models import Model, ModelType
 from llama_stack.models.llama.datatypes import ToolDefinition, ToolPromptFormat
-from llama_stack.providers.utils.inference import (
-    ALL_HUGGINGFACE_REPOS_TO_MODEL_DESCRIPTOR,
-)
 from llama_stack.providers.utils.inference.model_registry import (
     ModelRegistryHelper,
 )
@@ -93,8 +89,12 @@ class NVIDIAInferenceAdapter(Inference, ModelRegistryHelper):
 
         self._config = config
 
+    async def query_available_models(self) -> list[str]:
+        """Query available models from the NVIDIA API."""
+        return [model.id async for model in self._get_client().models.list()]
+
     @lru_cache  # noqa: B019
-    def _get_client(self, provider_model_id: str) -> AsyncOpenAI:
+    def _get_client(self, provider_model_id: str | None = None) -> AsyncOpenAI:
         """
         For hosted models, https://integrate.api.nvidia.com/v1 is the primary base_url. However,
         some models are hosted on different URLs. This function returns the appropriate client
@@ -103,7 +103,7 @@ class NVIDIAInferenceAdapter(Inference, ModelRegistryHelper):
         This relies on lru_cache and self._default_client to avoid creating a new client for each request
         or for each model that is hosted on https://integrate.api.nvidia.com/v1.
 
-        :param provider_model_id: The provider model ID
+        :param provider_model_id: The provider model ID (optional, defaults to primary endpoint)
         :return: An OpenAI client
         """
 
@@ -125,7 +125,7 @@ class NVIDIAInferenceAdapter(Inference, ModelRegistryHelper):
 
         base_url = f"{self._config.url}/v1" if self._config.append_api_version else self._config.url
 
-        if _is_nvidia_hosted(self._config) and provider_model_id in special_model_urls:
+        if provider_model_id and _is_nvidia_hosted(self._config) and provider_model_id in special_model_urls:
             base_url = special_model_urls[provider_model_id]
         return _get_client_for_base_url(base_url)
 
@@ -401,44 +401,3 @@ class NVIDIAInferenceAdapter(Inference, ModelRegistryHelper):
             return await self._get_client(provider_model_id).chat.completions.create(**params)
         except APIConnectionError as e:
             raise ConnectionError(f"Failed to connect to NVIDIA NIM at {self._config.url}: {e}") from e
-
-    async def register_model(self, model: Model) -> Model:
-        """
-        Allow non-llama model registration.
-
-        Non-llama model registration: API Catalogue models, post-training models, etc.
-            client = LlamaStackAsLibraryClient("nvidia")
-            client.models.register(
-                    model_id="mistralai/mixtral-8x7b-instruct-v0.1",
-                    model_type=ModelType.llm,
-                    provider_id="nvidia",
-                    provider_model_id="mistralai/mixtral-8x7b-instruct-v0.1"
-            )
-
-            NOTE: Only supports models endpoints compatible with AsyncOpenAI base_url format.
-        """
-        if model.model_type == ModelType.embedding:
-            # embedding models are always registered by their provider model id and does not need to be mapped to a llama model
-            provider_resource_id = model.provider_resource_id
-        else:
-            provider_resource_id = self.get_provider_model_id(model.provider_resource_id)
-
-        if provider_resource_id:
-            model.provider_resource_id = provider_resource_id
-        else:
-            llama_model = model.metadata.get("llama_model")
-            existing_llama_model = self.get_llama_model(model.provider_resource_id)
-            if existing_llama_model:
-                if existing_llama_model != llama_model:
-                    raise ValueError(
-                        f"Provider model id '{model.provider_resource_id}' is already registered to a different llama model: '{existing_llama_model}'"
-                    )
-            else:
-                # not llama model
-                if llama_model in ALL_HUGGINGFACE_REPOS_TO_MODEL_DESCRIPTOR:
-                    self.provider_id_to_llama_model_map[model.provider_resource_id] = (
-                        ALL_HUGGINGFACE_REPOS_TO_MODEL_DESCRIPTOR[llama_model]
-                    )
-                else:
-                    self.alias_to_provider_id_map[model.provider_model_id] = model.provider_model_id
-        return model