fixes and linting

llama_stack/providers/remote/inference/fireworks/fireworks.py

@@ -56,9 +56,7 @@ from .models import MODEL_ENTRIES
 logger = get_logger(name=__name__, category="inference")
 
 
-class FireworksInferenceAdapter(
-    ModelRegistryHelper, Inference, NeedsRequestProviderData
-):
+class FireworksInferenceAdapter(ModelRegistryHelper, Inference, NeedsRequestProviderData):
     def __init__(self, config: FireworksImplConfig) -> None:
         ModelRegistryHelper.__init__(self, MODEL_ENTRIES)
         self.config = config
@@ -70,9 +68,7 @@ class FireworksInferenceAdapter(
         pass
 
     def _get_api_key(self) -> str:
-        config_api_key = (
-            self.config.api_key.get_secret_value() if self.config.api_key else None
-        )
+        config_api_key = self.config.api_key.get_secret_value() if self.config.api_key else None
         if config_api_key:
             return config_api_key
         else:
@@ -112,9 +108,7 @@ class FireworksInferenceAdapter(
         else:
             return await self._nonstream_completion(request)
 
-    async def _nonstream_completion(
-        self, request: CompletionRequest
-    ) -> CompletionResponse:
+    async def _nonstream_completion(self, request: CompletionRequest) -> CompletionResponse:
         params = await self._get_params(request)
         r = await self._get_client().completion.acreate(**params)
         return process_completion_response(r)
@@ -194,9 +188,7 @@ class FireworksInferenceAdapter(
         else:
             return await self._nonstream_chat_completion(request)
 
-    async def _nonstream_chat_completion(
-        self, request: ChatCompletionRequest
-    ) -> ChatCompletionResponse:
+    async def _nonstream_chat_completion(self, request: ChatCompletionRequest) -> ChatCompletionResponse:
         params = await self._get_params(request)
         if "messages" in params:
             r = await self._get_client().chat.completions.acreate(**params)
@@ -204,9 +196,7 @@ class FireworksInferenceAdapter(
             r = await self._get_client().completion.acreate(**params)
         return process_chat_completion_response(r, request)
 
-    async def _stream_chat_completion(
-        self, request: ChatCompletionRequest
-    ) -> AsyncGenerator:
+    async def _stream_chat_completion(self, request: ChatCompletionRequest) -> AsyncGenerator:
         params = await self._get_params(request)
 
         async def _to_async_generator():
@@ -221,9 +211,7 @@ class FireworksInferenceAdapter(
         async for chunk in process_chat_completion_stream_response(stream, request):
             yield chunk
 
-    async def _get_params(
-        self, request: Union[ChatCompletionRequest, CompletionRequest]
-    ) -> dict:
+    async def _get_params(self, request: Union[ChatCompletionRequest, CompletionRequest]) -> dict:
         input_dict = {}
         media_present = request_has_media(request)
 
@@ -231,17 +219,12 @@ class FireworksInferenceAdapter(
         if isinstance(request, ChatCompletionRequest):
             if media_present or not llama_model:
                 input_dict["messages"] = [
-                    await convert_message_to_openai_dict(m, download=True)
-                    for m in request.messages
+                    await convert_message_to_openai_dict(m, download=True) for m in request.messages
                 ]
             else:
-                input_dict["prompt"] = await chat_completion_request_to_prompt(
-                    request, llama_model
-                )
+                input_dict["prompt"] = await chat_completion_request_to_prompt(request, llama_model)
         else:
-            assert (
-                not media_present
-            ), "Fireworks does not support media for Completion requests"
+            assert not media_present, "Fireworks does not support media for Completion requests"
             input_dict["prompt"] = await completion_request_to_prompt(request)
 
         # Fireworks always prepends with BOS
@@ -253,9 +236,7 @@ class FireworksInferenceAdapter(
             "model": request.model,
             **input_dict,
             "stream": request.stream,
-            **self._build_options(
-                request.sampling_params, request.response_format, request.logprobs
-            ),
+            **self._build_options(request.sampling_params, request.response_format, request.logprobs),
         }
         logger.debug(f"params to fireworks: {params}")
 
@@ -274,9 +255,9 @@ class FireworksInferenceAdapter(
         kwargs = {}
         if model.metadata.get("embedding_dimension"):
             kwargs["dimensions"] = model.metadata.get("embedding_dimension")
-        assert all(
-            not content_has_media(content) for content in contents
-        ), "Fireworks does not support media for embeddings"
+        assert all(not content_has_media(content) for content in contents), (
+            "Fireworks does not support media for embeddings"
+        )
         response = self._get_client().embeddings.create(
             model=model.provider_resource_id,
             input=[interleaved_content_as_str(content) for content in contents],