chore: remove vision model URL workarounds and simplify client creation

The vision models are now available at the standard URL, so the workaround
code has been removed. This also simplifies the codebase by eliminating
the need for per-model client caching.

- Remove special URL handling for meta/llama-3.2-11b/90b-vision-instruct models
- Convert _get_client method to _client property for cleaner API
- Remove unnecessary lru_cache decorator and functools import
- Simplify client creation logic to use single base URL for all models

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

@@ -7,7 +7,6 @@
 import logging
 import warnings
 from collections.abc import AsyncIterator
-from functools import lru_cache
 from typing import Any
 
 from openai import APIConnectionError, AsyncOpenAI, BadRequestError
@@ -93,41 +92,21 @@ class NVIDIAInferenceAdapter(Inference, ModelRegistryHelper):
 
         self._config = config
 
-    @lru_cache  # noqa: B019
+    @property
-    def _get_client(self, provider_model_id: str) -> AsyncOpenAI:
+    def _client(self) -> AsyncOpenAI:
         """
-        For hosted models, https://integrate.api.nvidia.com/v1 is the primary base_url. However,
+        Returns an OpenAI client for the configured NVIDIA API endpoint.
-        some models are hosted on different URLs. This function returns the appropriate client
-        for the given provider_model_id.
 
-        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
         :return: An OpenAI client
         """
 
-        @lru_cache  # noqa: B019
-        def _get_client_for_base_url(base_url: str) -> AsyncOpenAI:
-            """
-            Maintain a single OpenAI client per base_url.
-            """
-            return AsyncOpenAI(
-                base_url=base_url,
-                api_key=(self._config.api_key.get_secret_value() if self._config.api_key else "NO KEY"),
-                timeout=self._config.timeout,
-            )
-
-        special_model_urls = {
-            "meta/llama-3.2-11b-vision-instruct": "https://ai.api.nvidia.com/v1/gr/meta/llama-3.2-11b-vision-instruct",
-            "meta/llama-3.2-90b-vision-instruct": "https://ai.api.nvidia.com/v1/gr/meta/llama-3.2-90b-vision-instruct",
-        }
-
         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:
+        return AsyncOpenAI(
-            base_url = special_model_urls[provider_model_id]
+            base_url=base_url,
-        return _get_client_for_base_url(base_url)
+            api_key=(self._config.api_key.get_secret_value() if self._config.api_key else "NO KEY"),
+            timeout=self._config.timeout,
+        )
 
     async def _get_provider_model_id(self, model_id: str) -> str:
         if not self.model_store:
@@ -169,7 +148,7 @@ class NVIDIAInferenceAdapter(Inference, ModelRegistryHelper):
         )
 
         try:
-            response = await self._get_client(provider_model_id).completions.create(**request)
+            response = await self._client.completions.create(**request)
         except APIConnectionError as e:
             raise ConnectionError(f"Failed to connect to NVIDIA NIM at {self._config.url}: {e}") from e
 
@@ -222,7 +201,7 @@ class NVIDIAInferenceAdapter(Inference, ModelRegistryHelper):
             extra_body["input_type"] = task_type_options[task_type]
 
         try:
-            response = await self._get_client(provider_model_id).embeddings.create(
+            response = await self._client.embeddings.create(
                 model=provider_model_id,
                 input=input,
                 extra_body=extra_body,
@@ -283,7 +262,7 @@ class NVIDIAInferenceAdapter(Inference, ModelRegistryHelper):
         )
 
         try:
-            response = await self._get_client(provider_model_id).chat.completions.create(**request)
+            response = await self._client.chat.completions.create(**request)
         except APIConnectionError as e:
             raise ConnectionError(f"Failed to connect to NVIDIA NIM at {self._config.url}: {e}") from e
 
@@ -339,7 +318,7 @@ class NVIDIAInferenceAdapter(Inference, ModelRegistryHelper):
         )
 
         try:
-            return await self._get_client(provider_model_id).completions.create(**params)
+            return await self._client.completions.create(**params)
         except APIConnectionError as e:
             raise ConnectionError(f"Failed to connect to NVIDIA NIM at {self._config.url}: {e}") from e
 
@@ -398,7 +377,7 @@ class NVIDIAInferenceAdapter(Inference, ModelRegistryHelper):
         )
 
         try:
-            return await self._get_client(provider_model_id).chat.completions.create(**params)
+            return await self._client.chat.completions.create(**params)
         except APIConnectionError as e:
             raise ConnectionError(f"Failed to connect to NVIDIA NIM at {self._config.url}: {e}") from e
 

tests/unit/providers/nvidia/test_supervised_fine_tuning.py

@@ -54,7 +54,8 @@ class TestNvidiaPostTraining(unittest.TestCase):
         self.mock_client.chat.completions.create = unittest.mock.AsyncMock()
         self.inference_mock_make_request = self.mock_client.chat.completions.create
         self.inference_make_request_patcher = patch(
-            "llama_stack.providers.remote.inference.nvidia.nvidia.NVIDIAInferenceAdapter._get_client",
+            "llama_stack.providers.remote.inference.nvidia.nvidia.NVIDIAInferenceAdapter._client",
+            new_callable=unittest.mock.PropertyMock,
             return_value=self.mock_client,
         )
         self.inference_make_request_patcher.start()