Ruff fixes

aana/api/api_generation.py

@@ -2,16 +2,16 @@
 from dataclasses import dataclass
 from enum import Enum
 from typing import Any, Optional
+
 from fastapi import FastAPI, File, Form, UploadFile
 from fastapi.responses import StreamingResponse
 from mobius_pipeline.node.socket import Socket
 from mobius_pipeline.pipeline.pipeline import Pipeline
-from pydantic import BaseModel, Field, create_model, parse_raw_as
+from pydantic import BaseModel, Field, ValidationError, create_model, parse_raw_as
 
 from aana.api.responses import AanaJSONResponse
 from aana.exceptions.general import MultipleFileUploadNotAllowed
 from aana.models.pydantic.exception_response import ExceptionResponseModel
-from pydantic import ValidationError
 
 
 async def run_pipeline(
@@ -94,8 +94,7 @@ class FileUploadField:
 
 @dataclass
 class EndpointOutput:
-    """
-    Class used to represent an endpoint output.
+    """Class used to represent an endpoint output.
 
     Attributes:
         name (str): Name of the output that should be returned by the endpoint.
@@ -128,8 +127,7 @@ class Endpoint:
     streaming: bool = False
 
     def __post_init__(self):
-        """
-        Post init method.
+        """Post init method.
 
         Creates dictionaries for fast lookup of outputs.
         """
@@ -167,15 +165,15 @@ def socket_to_field(self, socket: Socket) -> tuple[Any, Any]:
         # to see if any of the fields are required
         try:
             data_model_instance = data_model()
-            return (data_model, data_model_instance)
         except ValidationError:
             # if we can't instantiate the data model
             # it means that it has required fields
             return (data_model, ...)
+        else:
+            return (data_model, data_model_instance)
 
     def get_input_fields(self, sockets: list[Socket]) -> dict[str, tuple[Any, Any]]:
-        """
-        Generate fields for the request Pydantic model based on the provided sockets.
+        """Generate fields for the request Pydantic model based on the provided sockets.
 
         Parameters:
             sockets (list[Socket]): List of sockets.
@@ -190,8 +188,7 @@ def get_input_fields(self, sockets: list[Socket]) -> dict[str, tuple[Any, Any]]:
         return fields
 
     def get_output_fields(self, sockets: list[Socket]) -> dict[str, tuple[Any, Any]]:
-        """
-        Generate fields for the response Pydantic model based on the provided sockets.
+        """Generate fields for the response Pydantic model based on the provided sockets.
 
         Parameters:
             sockets (list[Socket]): List of sockets.
@@ -294,8 +291,7 @@ def get_response_model(self, output_sockets: list[Socket]) -> type[BaseModel]:
         return ResponseModel
 
     def process_output(self, output: dict[str, Any]) -> dict[str, Any]:
-        """
-        Process the output of the pipeline.
+        """Process the output of the pipeline.
 
         Maps the output names of the pipeline to the names defined in the endpoint outputs.
 
@@ -366,7 +362,7 @@ async def route_func_body(body: str, files: list[UploadFile] | None = None):
             if self.streaming:
 
                 async def generator_wrapper() -> AsyncGenerator[bytes, None]:
-                    """Serializes the output of the generator using ORJSONResponseCustom"""
+                    """Serializes the output of the generator using ORJSONResponseCustom."""
                     async for output in run_pipeline_streaming(
                         pipeline, data_dict, outputs
                     ):

aana/deployments/hf_blip2_deployment.py

@@ -1,7 +1,7 @@
 from typing import Any, TypedDict
 
 import torch
-from pydantic import BaseModel, Field, validator
+from pydantic import BaseModel, Field
 from ray import serve
 from transformers import Blip2ForConditionalGeneration, Blip2Processor
 

aana/deployments/whisper_deployment.py

@@ -177,8 +177,7 @@ async def transcribe(
     async def transcribe_stream(
         self, media: Video, params: WhisperParams | None = None
     ) -> AsyncGenerator[WhisperOutput, None]:
-        """
-        Transcribe the media with the whisper model in a streaming fashion.
+        """Transcribe the media with the whisper model in a streaming fashion.
 
         Right now this is the same as transcribe, but we will add support for
         streaming in the future to support larger media and to make the ASR more responsive.

aana/tests/test_frame_extraction.py

@@ -48,11 +48,11 @@ def test_extract_frames_success(
 def test_generate_frames_success(
     video_name, extract_fps, fast_mode_enabled, expected_duration, expected_num_frames
 ):
-    """
-    Test that generator generate_frames_decord can be used
-    to extract frames from a video successfully.
-    """
+    """Test generate_frames_decord.
 
+    generate_frames_decord is a generator function that yields a dictionary
+    containing the frames, timestamps and duration of the video.
+    """
     video_path = resources.path("aana.tests.files.videos", video_name)
     video = Video(path=video_path)
     params = VideoParams(extract_fps=extract_fps, fast_mode_enabled=fast_mode_enabled)

aana/utils/video.py

@@ -6,6 +6,7 @@
 import numpy as np
 import yt_dlp
 from yt_dlp.utils import DownloadError
+
 from aana.configs.settings import settings
 from aana.exceptions.general import DownloadException, VideoReadingException
 from aana.models.core.image import Image
@@ -67,8 +68,7 @@ def extract_frames_decord(video: Video, params: VideoParams) -> FramesDict:
 def generate_frames_decord(
     video: Video, params: VideoParams, batch_size: int = 8
 ) -> Generator[FramesDict, None, None]:
-    """
-    Generate frames from a video using decord.
+    """Generate frames from a video using decord.
 
     Args:
         video (Video): the video to extract frames from
@@ -79,7 +79,6 @@ def generate_frames_decord(
         FramesDict: a dictionary containing the extracted frames, timestamps,
                     and duration for each batch
     """
-
     device = decord.cpu(0)
     num_threads = 1  # TODO: see if we can use more threads
 
@@ -117,8 +116,7 @@ def generate_frames_decord(
 
 
 def download_video(video_input: VideoInput | Video) -> Video:
-    """
-    Downloads videos for a VideoInput object.
+    """Downloads videos for a VideoInput object.
 
     Args:
         video_input (VideoInput): the video input to download

pyproject.toml

@@ -28,9 +28,6 @@ torch = { url = "https://download.pytorch.org/whl/cu118/torch-2.0.1%2Bcu118-cp31
 torchvision = { url = "https://download.pytorch.org/whl/cu118/torchvision-0.15.2%2Bcu118-cp310-cp310-linux_x86_64.whl" }
 vllm = "^0.2.1.post1"
 yt-dlp = "^2023.10.13"
-qdrant-client = "^1.6.9"
-bitsandbytes = "^0.41.2.post2"
-accelerate = "^0.24.1"
 
 [tool.poetry.group.dev.dependencies]
 ipykernel = "^6.25.2"