Update app.py

app.py

@@ -86,19 +86,15 @@ def process_video(radio, video, target_language, has_closeup_face):
     shell_command = f"ffmpeg -y -i {run_uuid}_output_audio.wav -af lowpass=3000,highpass=100 {run_uuid}_output_audio_final.wav".split(" ")
     subprocess.run([item for item in shell_command], capture_output=False, text=True, check=True)
     
-    segments, info = model.transcribe(f"{run_uuid}_output_audio_final.wav", beam_size=5)
+    segments, info = model.transcribe(f"{run_uuid}_output_audio_final.wav", beam_size=4)
     whisper_text = " ".join(segment.text for segment in segments)
     whisper_language = info.language
             
     language_mapping = {'English': 'en', 'Spanish': 'es', 'French': 'fr', 'German': 'de', 'Italian': 'it', 'Portuguese': 'pt', 'Polish': 'pl', 'Turkish': 'tr', 'Russian': 'ru', 'Dutch': 'nl', 'Czech': 'cs', 'Arabic': 'ar', 'Chinese (Simplified)': 'zh-cn'}
     target_language_code = language_mapping[target_language]
     translator = Translator()
-    try:
-        translated_text = translator.translate(whisper_text, src=whisper_language, dest=target_language_code).text
-        print(translated_text)
-    except AttributeError as e:
-        print("Failed to translate text. Likely an issue with token extraction in the Google Translate API.")
-        translated_text = "Translation failed due to API issue."
+    translated_text = translator.translate(whisper_text, src=whisper_language, dest=target_language_code).text
+    print(translated_text)
 
     tts = TTS("tts_models/multilingual/multi-dataset/xtts_v1")
     tts.to('cuda')