From 6c5c3b3d562ffc2ef042735ff9ab5f33c4c992f7 Mon Sep 17 00:00:00 2001
From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com>
Date: Sat, 15 Nov 2025 23:48:38 +0000
Subject: [PATCH] Fix critical code quality issues: remove unused imports, fix
 f-strings and whitespace

Co-authored-by: ariavn-byte <151469489+ariavn-byte@users.noreply.github.com>
---
 farsi_transcriber/config.py                     | 1 -
 farsi_transcriber/models/whisper_transcriber.py | 3 +--
 whisper/transcribe.py                           | 6 +++---
 whisper/utils.py                                | 2 +-
 4 files changed, 5 insertions(+), 7 deletions(-)

diff --git a/farsi_transcriber/config.py b/farsi_transcriber/config.py
index d5bb631..306adc7 100644
--- a/farsi_transcriber/config.py
+++ b/farsi_transcriber/config.py
@@ -4,7 +4,6 @@ Configuration settings for Farsi Transcriber application
 Manages model selection, device settings, and other configuration options.
 """
 
-import os
 from pathlib import Path
 
 # Application metadata
diff --git a/farsi_transcriber/models/whisper_transcriber.py b/farsi_transcriber/models/whisper_transcriber.py
index 8310cca..b7c6b37 100644
--- a/farsi_transcriber/models/whisper_transcriber.py
+++ b/farsi_transcriber/models/whisper_transcriber.py
@@ -4,7 +4,6 @@ Whisper Transcriber Module
 Handles Farsi audio/video transcription using OpenAI's Whisper model.
 """
 
-import os
 import warnings
 from pathlib import Path
 from typing import Dict, List, Optional
@@ -53,7 +52,7 @@ class FarsiTranscriber:
             warnings.simplefilter("ignore")
             self.model = whisper.load_model(model_name, device=self.device)
 
-        print(f"Model loaded successfully")
+        print("Model loaded successfully")
 
     def transcribe(
         self,
diff --git a/whisper/transcribe.py b/whisper/transcribe.py
index 0a4cc36..8eb1711 100644
--- a/whisper/transcribe.py
+++ b/whisper/transcribe.py
@@ -281,7 +281,7 @@ def transcribe(
             time_offset = float(seek * HOP_LENGTH / SAMPLE_RATE)
             window_end_time = float((seek + N_FRAMES) * HOP_LENGTH / SAMPLE_RATE)
             segment_size = min(N_FRAMES, content_frames - seek, seek_clip_end - seek)
-            mel_segment = mel[:, seek : seek + segment_size]
+            mel_segment = mel[:, seek:seek + segment_size]
             segment_duration = segment_size * HOP_LENGTH / SAMPLE_RATE
             mel_segment = pad_or_trim(mel_segment, N_FRAMES).to(model.device).to(dtype)
 
@@ -444,7 +444,7 @@ def transcribe(
                             continue
                         if is_segment_anomaly(segment):
                             next_segment = next_words_segment(
-                                current_segments[si + 1 :]
+                                current_segments[si + 1:]
                             )
                             if next_segment is not None:
                                 hal_next_start = next_segment["words"][0]["start"]
@@ -508,7 +508,7 @@ def transcribe(
             pbar.update(min(content_frames, seek) - previous_seek)
 
     return dict(
-        text=tokenizer.decode(all_tokens[len(initial_prompt_tokens) :]),
+        text=tokenizer.decode(all_tokens[len(initial_prompt_tokens):]),
         segments=all_segments,
         language=language,
     )
diff --git a/whisper/utils.py b/whisper/utils.py
index 13792f7..6ca958e 100644
--- a/whisper/utils.py
+++ b/whisper/utils.py
@@ -153,7 +153,7 @@ class SubtitlesWriter(ResultWriter):
                     if max_words_per_line > len(segment["words"]) - chunk_index:
                         words_count = remaining_words
                     for i, original_timing in enumerate(
-                        segment["words"][chunk_index : chunk_index + words_count]
+                        segment["words"][chunk_index:chunk_index + words_count]
                     ):
                         timing = original_timing.copy()
                         long_pause = (