refactor according to repo updates

llama_stack/providers/remote/inference/nutanix/__init__.py

@@ -7,6 +7,7 @@
 from .config import NutanixImplConfig
 from .nutanix import NutanixInferenceAdapter
 
+
 async def get_adapter_impl(config: NutanixInferenceAdapter, _deps):
     assert isinstance(
         config, NutanixImplConfig

llama_stack/providers/remote/inference/nutanix/config.py

@@ -4,8 +4,6 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-from typing import Optional
-
 from llama_models.schema_utils import json_schema_type
 from pydantic import BaseModel, Field
 

llama_stack/providers/remote/inference/nutanix/nutanix.py

@@ -14,7 +14,10 @@ from llama_models.llama3.api.datatypes import Message
 from llama_models.llama3.api.tokenizer import Tokenizer
 
 from llama_stack.apis.inference import *  # noqa: F403
-from llama_stack.providers.utils.inference.model_registry import ModelRegistryHelper
+from llama_stack.providers.utils.inference.model_registry import (
+    build_model_alias,
+    ModelRegistryHelper,    
+) 
 from llama_stack.providers.utils.inference.openai_compat import (
     get_sampling_options,
     process_chat_completion_response,
@@ -26,16 +29,18 @@ from llama_stack.providers.utils.inference.prompt_adapter import (
 
 from .config import NutanixImplConfig
 
-NUTANIX_SUPPORTED_MODELS = {
-    "Llama3.1-8B-Instruct": "vllm-llama-3-1",
-}
+
+model_aliases = [
+    build_model_alias(
+        "vllm-llama-3-1",
+        CoreModelId.llama3_1_8b_instruct.value,
+    ),
+]
 
 
 class NutanixInferenceAdapter(ModelRegistryHelper, Inference):
     def __init__(self, config: NutanixImplConfig) -> None:
-        ModelRegistryHelper.__init__(
-            self, stack_to_provider_models_map=NUTANIX_SUPPORTED_MODELS
-        )
+        ModelRegistryHelper.__init__(self, model_aliases)
         self.config = config
         self.formatter = ChatFormat(Tokenizer.get_instance())
 
@@ -47,7 +52,7 @@ class NutanixInferenceAdapter(ModelRegistryHelper, Inference):
 
     async def completion(
         self,
-        model: str,
+        model_id: str,
         content: InterleavedTextMedia,
         sampling_params: Optional[SamplingParams] = SamplingParams(),
         response_format: Optional[ResponseFormat] = None,
@@ -58,7 +63,7 @@ class NutanixInferenceAdapter(ModelRegistryHelper, Inference):
 
     async def chat_completion(
         self,
-        model: str,
+        model_id: str,
         messages: List[Message],
         sampling_params: Optional[SamplingParams] = SamplingParams(),
         response_format: Optional[ResponseFormat] = None,
@@ -110,8 +115,10 @@ class NutanixInferenceAdapter(ModelRegistryHelper, Inference):
 
     def _get_params(self, request: ChatCompletionRequest) -> dict:
         params = {
-            "model": self.map_to_provider_model(request.model),
-            "messages": chat_completion_request_to_messages(request, return_dict=True),
+            "model": request.model,
+            "messages": chat_completion_request_to_messages(
+                request, self.get_llama_model(request.model), return_dict=True
+            ),
             "stream": request.stream,
             **get_sampling_options(request.sampling_params),
         }
@@ -119,7 +126,7 @@ class NutanixInferenceAdapter(ModelRegistryHelper, Inference):
 
     async def embeddings(
         self,
-        model: str,
+        model_id: str,
         contents: List[InterleavedTextMedia],
     ) -> EmbeddingsResponse:
         raise NotImplementedError()

llama_stack/templates/nutanix/build.yaml

@@ -3,7 +3,7 @@ distribution_spec:
   description: Use Nutanix AI Endpoint for running LLM inference
   providers:
     inference: remote::nutanix
-    memory: meta-reference
-    safety: meta-reference
-    agents: meta-reference
-    telemetry: meta-reference
+    memory: inline::faiss
+    safety: inline::llama-guard
+    agents: inline::meta-reference
+    telemetry: inline::meta-reference