diff --git a/app/__init__.py b/app/__init__.py
index 7203803..c9c13e0 100644
--- a/app/__init__.py
+++ b/app/__init__.py
@@ -2,7 +2,7 @@
 from flask_cors import CORS
 from flask_restx import Api 
 
-from app.utils.logger import requests_logger,logger
+from app.utils.logger import requests_logger
 
 from app.routes import register_routes
 
diff --git a/app/models/whisper_model.py b/app/models/whisper_model.py
index 9217bf2..8da53c3 100644
--- a/app/models/whisper_model.py
+++ b/app/models/whisper_model.py
@@ -1,7 +1,5 @@
 """
 This module defines the WhisperTranscript class, which is a PyTorch model for transcribing audio files using the OpenAI Whisper model.
-"""
-import torch
 import torch.nn as nn
 
 from transformers import pipeline
diff --git a/app/routes/audio_transcript_sentiment_routes.py b/app/routes/audio_transcript_sentiment_routes.py
index 624bf63..c613d02 100644
--- a/app/routes/audio_transcript_sentiment_routes.py
+++ b/app/routes/audio_transcript_sentiment_routes.py
@@ -141,7 +141,7 @@ def post(self):
                 }, 200
 
 
-            except Exception as e:
+            except Exception:
                 return {
                     'status': 'error',
                     'error': 'An unexpected error occurred while processing the request.', # Generic error message
diff --git a/app/services/audio_transcription_sentiment_pipeline.py b/app/services/audio_transcription_sentiment_pipeline.py
index c7b641b..7f7ecf3 100644
--- a/app/services/audio_transcription_sentiment_pipeline.py
+++ b/app/services/audio_transcription_sentiment_pipeline.py
@@ -100,7 +100,6 @@ def process(self, url: str, start_time_ms: int, end_time_ms: int = None, user_id
 
             # Step(3) Perform sentiment [Per chunk :D]
             for chunk in chunks:
-                timestamp = chunk['timestamp']
                 text = chunk['text']
 
                 sentiment_result = self.sentiment_service.analyze(text)