Use our own pydantic models for OpenAI Server APIs

Importing the models from the OpenAI client library required a
top-level dependency on the openai python package, and also was
incompatible with our API generation code due to some quirks in how
the OpenAI pydantic models are defined.

So, this creates our own stubs of those pydantic models so that we're
in more direct control of our API surface for this OpenAI-compatible
API, so that it works with our code generation, and so that the openai
python client isn't a hard requirement of Llama Stack's API.

llama_stack/apis/models/models.py

@@ -7,7 +7,6 @@
 from enum import Enum
 from typing import Any, Dict, List, Literal, Optional, Protocol, runtime_checkable
 
-from openai.types.model import Model as OpenAIModel
 from pydantic import BaseModel, ConfigDict, Field
 
 from llama_stack.apis.resource import Resource, ResourceType
@@ -57,6 +56,22 @@ class ListModelsResponse(BaseModel):
     data: List[Model]
 
 
+@json_schema_type
+class OpenAIModel(BaseModel):
+    """A model from OpenAI.
+
+    :id: The ID of the model
+    :object: The object type, which will be "model"
+    :created: The Unix timestamp in seconds when the model was created
+    :owned_by: The owner of the model
+    """
+
+    id: str
+    object: Literal["model"] = "model"
+    created: int
+    owned_by: str
+
+
 class OpenAIListModelsResponse(BaseModel):
     data: List[OpenAIModel]