models endpoint testing

llama_stack/providers/adapters/inference/fireworks/fireworks.py

@@ -6,14 +6,14 @@
 
 from typing import AsyncGenerator
 
+from fireworks.client import Fireworks
+
 from llama_models.llama3.api.chat_format import ChatFormat
 
 from llama_models.llama3.api.datatypes import Message, StopReason
 from llama_models.llama3.api.tokenizer import Tokenizer
 from llama_models.sku_list import resolve_model
 
-from fireworks.client import Fireworks
-
 from llama_stack.apis.inference import *  # noqa: F403
 from llama_stack.providers.utils.inference.prepare_messages import prepare_messages
 
@@ -42,7 +42,14 @@ class FireworksInferenceAdapter(Inference):
     async def shutdown(self) -> None:
         pass
 
-    async def completion(self, request: CompletionRequest) -> AsyncGenerator:
+    async def completion(
+        self,
+        model: str,
+        content: InterleavedTextMedia,
+        sampling_params: Optional[SamplingParams] = SamplingParams(),
+        stream: Optional[bool] = False,
+        logprobs: Optional[LogProbConfig] = None,
+    ) -> AsyncGenerator:
         raise NotImplementedError()
 
     def _messages_to_fireworks_messages(self, messages: list[Message]) -> list:

llama_stack/providers/adapters/inference/ollama/ollama.py

@@ -30,25 +30,33 @@ OLLAMA_SUPPORTED_SKUS = {
 class OllamaInferenceAdapter(Inference):
     def __init__(self, url: str) -> None:
         self.url = url
-        tokenizer = Tokenizer.get_instance()
-        self.formatter = ChatFormat(tokenizer)
+        # tokenizer = Tokenizer.get_instance()
+        # self.formatter = ChatFormat(tokenizer)
 
     @property
     def client(self) -> AsyncClient:
         return AsyncClient(host=self.url)
 
     async def initialize(self) -> None:
-        try:
-            await self.client.ps()
-        except httpx.ConnectError as e:
-            raise RuntimeError(
-                "Ollama Server is not running, start it using `ollama serve` in a separate terminal"
-            ) from e
+        print("Ollama init")
+        # try:
+        #     await self.client.ps()
+        # except httpx.ConnectError as e:
+        #     raise RuntimeError(
+        #         "Ollama Server is not running, start it using `ollama serve` in a separate terminal"
+        #     ) from e
 
     async def shutdown(self) -> None:
         pass
 
-    async def completion(self, request: CompletionRequest) -> AsyncGenerator:
+    async def completion(
+        self,
+        model: str,
+        content: InterleavedTextMedia,
+        sampling_params: Optional[SamplingParams] = SamplingParams(),
+        stream: Optional[bool] = False,
+        logprobs: Optional[LogProbConfig] = None,
+    ) -> AsyncGenerator:
         raise NotImplementedError()
 
     def _messages_to_ollama_messages(self, messages: list[Message]) -> list:

llama_stack/providers/adapters/inference/tgi/tgi.py

@@ -54,7 +54,14 @@ class TGIAdapter(Inference):
     async def shutdown(self) -> None:
         pass
 
-    async def completion(self, request: CompletionRequest) -> AsyncGenerator:
+    async def completion(
+        self,
+        model: str,
+        content: InterleavedTextMedia,
+        sampling_params: Optional[SamplingParams] = SamplingParams(),
+        stream: Optional[bool] = False,
+        logprobs: Optional[LogProbConfig] = None,
+    ) -> AsyncGenerator:
         raise NotImplementedError()
 
     def get_chat_options(self, request: ChatCompletionRequest) -> dict:

llama_stack/providers/adapters/inference/together/together.py

@@ -42,7 +42,14 @@ class TogetherInferenceAdapter(Inference):
     async def shutdown(self) -> None:
         pass
 
-    async def completion(self, request: CompletionRequest) -> AsyncGenerator:
+    async def completion(
+        self,
+        model: str,
+        content: InterleavedTextMedia,
+        sampling_params: Optional[SamplingParams] = SamplingParams(),
+        stream: Optional[bool] = False,
+        logprobs: Optional[LogProbConfig] = None,
+    ) -> AsyncGenerator:
         raise NotImplementedError()
 
     def _messages_to_together_messages(self, messages: list[Message]) -> list: