feat: create dynamic model registration for OpenAI and Llama compat remote inference providers (#2745)

# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to
relevant issues if applicable. -->
The purpose of this task is to create a solution that can automatically
detect when new models are added, deprecated, or removed by OpenAI and
Llama API providers, and automatically update the list of supported
models in LLamaStack.

This feature is vitally important in order to avoid missing new models
and editing the entries manually hence I created automation allowing
users to dynamically register:
- any models from OpenAI provider available at 
[https://api.openai.com/v1/models](https://api.openai.com/v1/models)
that are not in
[https://github.com/meta-llama/llama-stack/blob/main/llama_stack/providers/remote/inference/openai/models.py](https://github.com/meta-llama/llama-stack/blob/main/llama_stack/providers/remote/inference/openai/models.py)

- any models from Llama API provider available at
[https://api.llama.com/v1/models](https://api.llama.com/v1/models) that
are not in
[https://github.com/meta-llama/llama-stack/blob/main/llama_stack/providers/remote/inference/llama_openai_compat/models.py](https://github.com/meta-llama/llama-stack/blob/main/llama_stack/providers/remote/inference/llama_openai_compat/models.py)

<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->
Closes #2504

this PR is dependant on #2710

## Test Plan
<!-- Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.* -->

1. Create venv at root llamastack directory:
`uv venv .venv --python 3.12 --seed`    
2. Activate venv:
`source .venv/bin/activate`   
3. `uv pip install -e .`
4. Create OpenAI distro modifying run.yaml
5. Build distro:
`llama stack build --template starter --image-type venv`
6. Then run LlamaStack, but before navigate to templates/starter folder:
`llama stack run run.yaml --image-type venv OPENAI_API_KEY=<YOUR_KEY>
ENABLE_OPENAI=openai`
7. Then try to register dummy llm that doesn't exist in OpenAI provider:
` llama-stack-client models register ianm/ianllm
--provider-model-id=ianllm --provider-id=openai `
 
You should receive this output - combined list of static config +
fetched available models from OpenAI:
 
<img width="1380" height="474" alt="Screenshot 2025-07-14 at 12 48 50"
src="https://github.com/user-attachments/assets/d26aad18-6b15-49ee-9c49-b01b2d33f883"
/>

8. Then register real llm from OpenAI:
llama-stack-client models register openai/gpt-4-turbo-preview
--provider-model-id=gpt-4-turbo-preview --provider-id=openai

<img width="1253" height="613" alt="Screenshot 2025-07-14 at 13 43 02"
src="https://github.com/user-attachments/assets/60a5c9b1-3468-4eb9-9e92-cd7d21de3ca0"
/>
<img width="1288" height="655" alt="Screenshot 2025-07-14 at 13 43 11"
src="https://github.com/user-attachments/assets/c1e48871-0e24-4bd9-a0b8-8c95552a51ee"
/>

We correctly fetched all available models from OpenAI

As for Llama API, as a non-US person I don't have access to Llama API
Key but I joined wait list. The implementation for Llama is the same as
for OpenAI since Llama is openai compatible. So, the response from GET
endpoint has the same structure as OpenAI
https://llama.developer.meta.com/docs/api/models

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

@@ -3,16 +3,17 @@
 #
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
+import logging
 
-from llama_stack.providers.remote.inference.llama_openai_compat.config import (
-    LlamaCompatConfig,
-)
-from llama_stack.providers.utils.inference.litellm_openai_mixin import (
-    LiteLLMOpenAIMixin,
-)
+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
 
 from .models import MODEL_ENTRIES
 
+logger = logging.getLogger(__name__)
+
 
 class LlamaCompatInferenceAdapter(LiteLLMOpenAIMixin):
     _config: LlamaCompatConfig
@@ -27,8 +28,32 @@ class LlamaCompatInferenceAdapter(LiteLLMOpenAIMixin):
         )
         self.config = config
 
+    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:
+            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.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,
@@ -60,6 +60,27 @@ class OpenAIInferenceAdapter(LiteLLMOpenAIMixin):
         # litellm specific model names, an abstraction leak.
         self.is_openai_compat = True
 
+    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()
+            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.error(f"Failed to check model availability from OpenAI: {e}")
+            return False
+
     async def initialize(self) -> None:
         await super().initialize()
 

llama_stack/providers/utils/inference/litellm_openai_mixin.py

@@ -13,7 +13,6 @@ from llama_stack.apis.common.content_types import (
     InterleavedContent,
     InterleavedContentItem,
 )
-from llama_stack.apis.common.errors import UnsupportedModelError
 from llama_stack.apis.inference import (
     ChatCompletionRequest,
     ChatCompletionResponse,
@@ -39,7 +38,6 @@ from llama_stack.apis.inference import (
     ToolDefinition,
     ToolPromptFormat,
 )
-from llama_stack.apis.models import Model
 from llama_stack.distribution.request_headers import NeedsRequestProviderData
 from llama_stack.log import get_logger
 from llama_stack.providers.utils.inference.model_registry import ModelRegistryHelper
@@ -90,12 +88,6 @@ class LiteLLMOpenAIMixin(
     async def shutdown(self):
         pass
 
-    async def register_model(self, model: Model) -> Model:
-        model_id = self.get_provider_model_id(model.provider_resource_id)
-        if model_id is None:
-            raise UnsupportedModelError(model.provider_resource_id, self.alias_to_provider_id_map.keys())
-        return model
-
     def get_litellm_model_name(self, model_id: str) -> str:
         # users may be using openai/ prefix in their model names. the openai/models.py did this by default.
         # model_id.startswith("openai/") is for backwards compatibility.

pyproject.toml

@@ -29,6 +29,7 @@ dependencies = [
     "jinja2>=3.1.6",
     "jsonschema",
     "llama-stack-client>=0.2.15",
+    "llama-api-client>=0.1.2",
     "openai>=1.66",
     "prompt-toolkit",
     "python-dotenv",

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

uv.lock

@@ -1268,6 +1268,23 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/2a/f7/67689245f48b9e79bcd2f3a10a3690cb1918fb99fffd5a623ed2496bca66/litellm-1.74.2-py3-none-any.whl", hash = "sha256:29bb555b45128e4cc696e72921a6ec24e97b14e9b69e86eed6f155124ad629b1", size = 8587065 },
 ]
 
+[[package]]
+name = "llama-api-client"
+version = "0.1.2"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "anyio" },
+    { name = "distro" },
+    { name = "httpx" },
+    { name = "pydantic" },
+    { name = "sniffio" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/d0/78/875de3a16efd0442718ac47cc27319cd80cc5f38e12298e454e08611acc4/llama_api_client-0.1.2.tar.gz", hash = "sha256:709011f2d506009b1b3b3bceea1c84f2a3a7600df1420fb256e680fcd7251387", size = 113695, upload-time = "2025-06-27T19:56:14.057Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/99/08/5d7e6e7e6af5353391376288c200acacebb8e6b156d3636eae598a451673/llama_api_client-0.1.2-py3-none-any.whl", hash = "sha256:8ad6e10726f74b2302bfd766c61c41355a9ecf60f57cde2961882d22af998941", size = 84091, upload-time = "2025-06-27T19:56:12.8Z" },
+]
+
 [[package]]
 name = "llama-stack"
 version = "0.2.15"
@@ -1283,6 +1300,7 @@ dependencies = [
     { name = "huggingface-hub" },
     { name = "jinja2" },
     { name = "jsonschema" },
+    { name = "llama-api-client" },
     { name = "llama-stack-client" },
     { name = "openai" },
     { name = "opentelemetry-exporter-otlp-proto-http" },
@@ -1398,6 +1416,7 @@ requires-dist = [
     { name = "jsonschema" },
     { name = "llama-stack-client", specifier = ">=0.2.15" },
     { name = "llama-stack-client", marker = "extra == 'ui'", specifier = ">=0.2.15" },
+    { name = "llama-api-client", specifier = ">=0.1.2" },
     { name = "openai", specifier = ">=1.66" },
     { name = "opentelemetry-exporter-otlp-proto-http", specifier = ">=1.30.0" },
     { name = "opentelemetry-sdk", specifier = ">=1.30.0" },