refactor: switched from query_available_models() to check_model_availability() in OpenAIInferenceAdapter and LlamaCompatInferenceAdapter

llama_stack/providers/remote/inference/llama_openai_compat/llama.py

@@ -5,7 +5,7 @@
 # the root directory of this source tree.
 import logging
 
-from llama_api_client import AsyncLlamaAPIClient
+from llama_api_client import AsyncLlamaAPIClient, NotFoundError
 
 from llama_stack.providers.remote.inference.llama_openai_compat.config import LlamaCompatConfig
 from llama_stack.providers.utils.inference.litellm_openai_mixin import LiteLLMOpenAIMixin
@@ -27,20 +27,33 @@ class LlamaCompatInferenceAdapter(LiteLLMOpenAIMixin):
             openai_compat_api_base=config.openai_compat_api_base,
         )
         self.config = config
-        self._llama_api_client = AsyncLlamaAPIClient(api_key=config.api_key)
 
-    async def query_available_models(self) -> list[str]:
-        """Query available models from the Llama API."""
+    async def check_model_availability(self, model: str) -> bool:
+        """
+        Check if a specific model is available from Llama API.
+
+        :param model: The model identifier to check.
+        :return: True if the model is available dynamically, False otherwise.
+        """
         try:
-            available_models = await self._llama_api_client.models.list()
-            logger.info(f"Available models from Llama API: {available_models}")
-            return [model.id for model in available_models]
+            llama_api_client = self._get_llama_api_client()
+            retrieved_model = await llama_api_client.models.retrieve(model)
+            logger.info(f"Model {retrieved_model.id} is available from Llama API")
+            return True
+
+        except NotFoundError:
+            logger.error(f"Model {model} is not available from Llama API")
+            return False
+
         except Exception as e:
-            logger.warning(f"Failed to query available models from Llama API: {e}")
-            return []
+            logger.error(f"Failed to check model availability from Llama API: {e}")
+            return False
 
     async def initialize(self):
         await super().initialize()
 
     async def shutdown(self):
         await super().shutdown()
+
+    def _get_llama_api_client(self) -> AsyncLlamaAPIClient:
+        return AsyncLlamaAPIClient(api_key=self.get_api_key(), base_url=self.config.openai_compat_api_base)

llama_stack/providers/remote/inference/openai/openai.py

@@ -8,7 +8,7 @@ import logging
 from collections.abc import AsyncIterator
 from typing import Any
 
-from openai import AsyncOpenAI
+from openai import AsyncOpenAI, NotFoundError
 
 from llama_stack.apis.inference import (
     OpenAIChatCompletion,
@@ -60,16 +60,26 @@ class OpenAIInferenceAdapter(LiteLLMOpenAIMixin):
         # litellm specific model names, an abstraction leak.
         self.is_openai_compat = True
 
-    async def query_available_models(self) -> list[str]:
-        """Query available models from the OpenAI API"""
+    async def check_model_availability(self, model: str) -> bool:
+        """
+        Check if a specific model is available from OpenAI.
+
+        :param model: The model identifier to check.
+        :return: True if the model is available dynamically, False otherwise.
+        """
         try:
             openai_client = self._get_openai_client()
-            available_models = await openai_client.models.list()
-            logger.info(f"Available models from OpenAI: {available_models.data}")
-            return [model.id for model in available_models.data]
+            retrieved_model = await openai_client.models.retrieve(model)
+            logger.info(f"Model {retrieved_model.id} is available from OpenAI")
+            return True
+
+        except NotFoundError:
+            logger.error(f"Model {model} is not available from OpenAI")
+            return False
+
         except Exception as e:
-            logger.warning(f"Failed to query available models from OpenAI: {e}")
-            return []
+            logger.error(f"Failed to check model availability from OpenAI: {e}")
+            return False
 
     async def initialize(self) -> None:
         await super().initialize()

requirements.txt

@@ -13,6 +13,7 @@ annotated-types==0.7.0
 anyio==4.8.0
     # via
     #   httpx
+    #   llama-api-client
     #   llama-stack-client
     #   openai
     #   starlette
@@ -49,6 +50,7 @@ deprecated==1.2.18
     #   opentelemetry-semantic-conventions
 distro==1.9.0
     # via
+    #   llama-api-client
     #   llama-stack-client
     #   openai
 ecdsa==0.19.1
@@ -80,6 +82,7 @@ httpcore==1.0.9
     # via httpx
 httpx==0.28.1
     # via
+    #   llama-api-client
     #   llama-stack
     #   llama-stack-client
     #   openai
@@ -101,6 +104,8 @@ jsonschema==4.23.0
     # via llama-stack
 jsonschema-specifications==2024.10.1
     # via jsonschema
+llama-api-client==0.1.2
+    # via llama-stack
 llama-stack-client==0.2.15
     # via llama-stack
 markdown-it-py==3.0.0
@@ -165,6 +170,7 @@ pycparser==2.22 ; platform_python_implementation != 'PyPy'
 pydantic==2.10.6
     # via
     #   fastapi
+    #   llama-api-client
     #   llama-stack
     #   llama-stack-client
     #   openai
@@ -215,6 +221,7 @@ six==1.17.0
 sniffio==1.3.1
     # via
     #   anyio
+    #   llama-api-client
     #   llama-stack-client
     #   openai
 starlette==0.45.3
@@ -239,6 +246,7 @@ typing-extensions==4.12.2
     #   anyio
     #   fastapi
     #   huggingface-hub
+    #   llama-api-client
     #   llama-stack-client
     #   openai
     #   opentelemetry-sdk