nitpick: minor refactoring

src/litserve/connector.py

@@ -22,28 +22,23 @@
 class _Connector:
     def __init__(self, accelerator: str = "auto", devices: Union[List[int], int, str] = "auto"):
         accelerator = self._sanitize_accelerator(accelerator)
-        if accelerator == "cpu":
-            self._accelerator = "cpu"
-        elif accelerator == "cuda":
-            self._accelerator = "cuda"
-        elif accelerator == "mps":
-            self._accelerator = "mps"
-
+        if accelerator in ("cpu", "cuda", "mps"):
+            self._accelerator = accelerator
         elif accelerator == "auto":
             self._accelerator = self._choose_auto_accelerator()
         elif accelerator == "gpu":
             self._accelerator = self._choose_gpu_accelerator_backend()
 
         if devices == "auto":
-            self._devices = self._auto_device_count(self._accelerator)
+            self._devices = self._accelerator_device_count()
         else:
             self._devices = devices
 
         self.check_devices_and_accelerators()
 
     def check_devices_and_accelerators(self):
         """Check if the devices are in a valid fomra and raise an error if they are not."""
-        if self._accelerator in ["cuda", "mps"]:
+        if self._accelerator in ("cuda", "mps"):
             if not isinstance(self._devices, int) and not (
                 isinstance(self._devices, list) and all(isinstance(device, int) for device in self._devices)
             ):
@@ -68,7 +63,7 @@ def _sanitize_accelerator(accelerator: Optional[str]):
             accelerator = accelerator.lower()
 
         if accelerator not in ["auto", "cpu", "mps", "cuda", "gpu", None]:
-            raise ValueError("accelerator must be one of 'auto', 'cpu', 'mps', 'cuda', or 'gpu'")
+            raise ValueError(f"accelerator must be one of 'auto', 'cpu', 'mps', 'cuda', or 'gpu'. Found: {accelerator}")
 
         if accelerator is None:
             return "auto"
@@ -80,8 +75,8 @@ def _choose_auto_accelerator(self):
             return gpu_backend
         return "cpu"
 
-    def _auto_device_count(self, accelerator) -> int:
-        if accelerator == "cuda":
+    def _accelerator_device_count(self) -> int:
+        if self._accelerator == "cuda":
             return check_cuda_with_nvidia_smi()
         return 1
 

src/litserve/loops/loops.py

@@ -28,15 +28,14 @@
 
 
 def get_default_loop(stream: bool, max_batch_size: int) -> _BaseLoop:
-    return (
-        BatchedStreamingLoop()
-        if stream and max_batch_size > 1
-        else StreamingLoop()
-        if stream
-        else BatchedLoop()
-        if max_batch_size > 1
-        else SingleLoop()
-    )
+    if stream:
+        if max_batch_size > 1:
+            return BatchedStreamingLoop()
+        return StreamingLoop()
+    else:  # noqa: RET505
+        if max_batch_size > 1:
+            return BatchedLoop()
+        return SingleLoop()
 
 
 def inference_worker(

src/litserve/server.py

@@ -443,7 +443,7 @@ async def info(request: Request) -> Response:
                 }
             )
 
-        async def predict(request: self.request_type) -> self.response_type:
+        async def predict(request: self.request_type) -> self.response_type:  # should be Any
             self._callback_runner.trigger_event(
                 EventTypes.ON_REQUEST,
                 active_requests=self.active_requests,
@@ -477,7 +477,7 @@ async def predict(request: self.request_type) -> self.response_type:
             self._callback_runner.trigger_event(EventTypes.ON_RESPONSE, litserver=self)
             return response
 
-        async def stream_predict(request: self.request_type) -> self.response_type:
+        async def stream_predict(request: self.request_type) -> self.response_type:  # should be Any
             self._callback_runner.trigger_event(
                 EventTypes.ON_REQUEST,
                 active_requests=self.active_requests,

src/litserve/specs/openai_embedding.py

@@ -16,7 +16,7 @@
 import logging
 import time
 import uuid
-from typing import List, Literal, Optional, Union
+from typing import TYPE_CHECKING, List, Literal, Optional, Union
 
 from fastapi import HTTPException, Request, Response, status
 from fastapi import status as status_code
@@ -27,6 +27,9 @@
 
 logger = logging.getLogger(__name__)
 
+if TYPE_CHECKING:
+    from litserve import LitServer
+
 
 class EmbeddingRequest(BaseModel):
     input: Union[str, List[str], List[int], List[List[int]]]
@@ -93,7 +96,7 @@ def __init__(self):
         self.add_endpoint("/v1/embeddings", self.embeddings, ["POST"])
         self.add_endpoint("/v1/embeddings", self.options_embeddings, ["GET"])
 
-    def setup(self, server: "LitServer"):  # noqa: F821
+    def setup(self, server: "LitServer"):
         from litserve import LitAPI
 
         super().setup(server)

src/litserve/transport/base.py

@@ -1,8 +1,6 @@
 from abc import ABC, abstractmethod
 from typing import Any, Optional
 
-# TODO: raise NotImplemented error for all methods
-
 
 class MessageTransport(ABC):
     @abstractmethod