chore: turn OpenAIMixin into a pydantic.BaseModel (#3671)

# What does this PR do?

- implement get_api_key instead of relying on
LiteLLMOpenAIMixin.get_api_key
 - remove use of LiteLLMOpenAIMixin
 - add default initialize/shutdown methods to OpenAIMixin
 - remove __init__s to allow proper pydantic construction
- remove dead code from vllm adapter and associated / duplicate unit
tests
 - update vllm adapter to use openaimixin for model registration
 - remove ModelRegistryHelper from fireworks & together adapters
 - remove Inference from nvidia adapter
 - complete type hints on embedding_model_metadata
- allow extra fields on OpenAIMixin, for model_store, __provider_id__,
etc
 - new recordings for ollama
 - enhance the list models error handling
- update cerebras (remove cerebras-cloud-sdk) and anthropic (custom
model listing) inference adapters
 - parametrized test_inference_client_caching
- remove cerebras, databricks, fireworks, together from blanket mypy
exclude
 - removed unnecessary litellm deps

## Test Plan

ci

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

@@ -11,6 +11,6 @@ async def get_adapter_impl(config: DatabricksImplConfig, _deps):
     from .databricks import DatabricksInferenceAdapter
 
     assert isinstance(config, DatabricksImplConfig), f"Unexpected config type: {type(config)}"
-    impl = DatabricksInferenceAdapter(config)
+    impl = DatabricksInferenceAdapter(config=config)
     await impl.initialize()
     return impl

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

@@ -14,12 +14,12 @@ from llama_stack.schema_utils import json_schema_type
 
 @json_schema_type
 class DatabricksImplConfig(RemoteInferenceProviderConfig):
-    url: str = Field(
+    url: str | None = Field(
         default=None,
         description="The URL for the Databricks model serving endpoint",
     )
     api_token: SecretStr = Field(
-        default=SecretStr(None),
+        default=SecretStr(None),  # type: ignore[arg-type]
         description="The Databricks API token",
     )
 

llama_stack/providers/remote/inference/databricks/databricks.py

@@ -9,10 +9,7 @@ from typing import Any
 
 from databricks.sdk import WorkspaceClient
 
-from llama_stack.apis.inference import (
-    Inference,
-    OpenAICompletion,
-)
+from llama_stack.apis.inference import OpenAICompletion
 from llama_stack.log import get_logger
 from llama_stack.providers.utils.inference.openai_mixin import OpenAIMixin
 
@@ -21,30 +18,31 @@ from .config import DatabricksImplConfig
 logger = get_logger(name=__name__, category="inference::databricks")
 
 
-class DatabricksInferenceAdapter(
-    OpenAIMixin,
-    Inference,
-):
+class DatabricksInferenceAdapter(OpenAIMixin):
+    config: DatabricksImplConfig
+
     # source: https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models
-    embedding_model_metadata = {
+    embedding_model_metadata: dict[str, dict[str, int]] = {
         "databricks-gte-large-en": {"embedding_dimension": 1024, "context_length": 8192},
         "databricks-bge-large-en": {"embedding_dimension": 1024, "context_length": 512},
     }
 
-    def __init__(self, config: DatabricksImplConfig) -> None:
-        self.config = config
-
     def get_api_key(self) -> str:
         return self.config.api_token.get_secret_value()
 
     def get_base_url(self) -> str:
         return f"{self.config.url}/serving-endpoints"
 
-    async def initialize(self) -> None:
-        return
+    async def list_provider_model_ids(self) -> Iterable[str]:
+        return [
+            endpoint.name
+            for endpoint in WorkspaceClient(
+                host=self.config.url, token=self.get_api_key()
+            ).serving_endpoints.list()  # TODO: this is not async
+        ]
 
-    async def shutdown(self) -> None:
-        pass
+    async def should_refresh_models(self) -> bool:
+        return False
 
     async def openai_completion(
         self,
@@ -70,14 +68,3 @@ class DatabricksInferenceAdapter(
         suffix: str | None = None,
     ) -> OpenAICompletion:
         raise NotImplementedError()
-
-    async def list_provider_model_ids(self) -> Iterable[str]:
-        return [
-            endpoint.name
-            for endpoint in WorkspaceClient(
-                host=self.config.url, token=self.get_api_key()
-            ).serving_endpoints.list()  # TODO: this is not async
-        ]
-
-    async def should_refresh_models(self) -> bool:
-        return False