ollama

llama_stack/providers/remote/inference/ollama/ollama.py

@@ -20,7 +20,7 @@ from llama_stack.providers.utils.inference.model_registry import (
 )
 
 from llama_stack.apis.inference import *  # noqa: F403
-from llama_stack.providers.datatypes import Model, ModelsProtocolPrivate
+from llama_stack.providers.datatypes import ModelsProtocolPrivate
 
 from llama_stack.providers.utils.inference.openai_compat import (
     get_sampling_options,
@@ -103,29 +103,6 @@ class OllamaInferenceAdapter(Inference, ModelRegistryHelper, ModelsProtocolPriva
     async def shutdown(self) -> None:
         pass
 
-    async def list_models(self) -> List[Model]:
-        ollama_to_llama = {v: k for k, v in OLLAMA_SUPPORTED_MODELS.items()}
-
-        ret = []
-        res = await self.client.ps()
-        for r in res["models"]:
-            if r["model"] not in ollama_to_llama:
-                print(f"Ollama is running a model unknown to Llama Stack: {r['model']}")
-                continue
-
-            llama_model = ollama_to_llama[r["model"]]
-            print(f"Found model {llama_model} in Ollama")
-            ret.append(
-                Model(
-                    identifier=llama_model,
-                    metadata={
-                        "ollama_model": r["model"],
-                    },
-                )
-            )
-
-        return ret
-
     async def completion(
         self,
         model_id: str,
@@ -243,7 +220,7 @@ class OllamaInferenceAdapter(Inference, ModelRegistryHelper, ModelsProtocolPriva
             input_dict["raw"] = True
 
         return {
-            "model": OLLAMA_SUPPORTED_MODELS[request.model],
+            "model": request.model,
             **input_dict,
             "options": sampling_options,
             "stream": request.stream,