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/cerebras/cerebras.py

@@ -6,39 +6,14 @@
 
 from urllib.parse import urljoin
 
-from cerebras.cloud.sdk import AsyncCerebras
-
-from llama_stack.apis.inference import (
-    ChatCompletionRequest,
-    CompletionRequest,
-    Inference,
-    OpenAIEmbeddingsResponse,
-    TopKSamplingStrategy,
-)
-from llama_stack.providers.utils.inference.openai_compat import (
-    get_sampling_options,
-)
+from llama_stack.apis.inference import OpenAIEmbeddingsResponse
 from llama_stack.providers.utils.inference.openai_mixin import OpenAIMixin
-from llama_stack.providers.utils.inference.prompt_adapter import (
-    chat_completion_request_to_prompt,
-    completion_request_to_prompt,
-)
 
 from .config import CerebrasImplConfig
 
 
-class CerebrasInferenceAdapter(
-    OpenAIMixin,
-    Inference,
-):
-    def __init__(self, config: CerebrasImplConfig) -> None:
-        self.config = config
-
-        # TODO: make this use provider data, etc. like other providers
-        self._cerebras_client = AsyncCerebras(
-            base_url=self.config.base_url,
-            api_key=self.config.api_key.get_secret_value(),
-        )
+class CerebrasInferenceAdapter(OpenAIMixin):
+    config: CerebrasImplConfig
 
     def get_api_key(self) -> str:
         return self.config.api_key.get_secret_value()
@@ -46,31 +21,6 @@ class CerebrasInferenceAdapter(
     def get_base_url(self) -> str:
         return urljoin(self.config.base_url, "v1")
 
-    async def initialize(self) -> None:
-        return
-
-    async def shutdown(self) -> None:
-        pass
-
-    async def _get_params(self, request: ChatCompletionRequest | CompletionRequest) -> dict:
-        if request.sampling_params and isinstance(request.sampling_params.strategy, TopKSamplingStrategy):
-            raise ValueError("`top_k` not supported by Cerebras")
-
-        prompt = ""
-        if isinstance(request, ChatCompletionRequest):
-            prompt = await chat_completion_request_to_prompt(request, self.get_llama_model(request.model))
-        elif isinstance(request, CompletionRequest):
-            prompt = await completion_request_to_prompt(request)
-        else:
-            raise ValueError(f"Unknown request type {type(request)}")
-
-        return {
-            "model": request.model,
-            "prompt": prompt,
-            "stream": request.stream,
-            **get_sampling_options(request.sampling_params),
-        }
-
     async def openai_embeddings(
         self,
         model: str,