Update app.py

app.py

@@ -3,12 +3,13 @@ import torch
 import gradio as gr
 import numpy as np
 from transformers import WhisperProcessor, WhisperForConditionalGeneration
-from googletrans_temp import Translator
+from deep_translator import GoogleTranslator
 from gtts import gTTS
 import librosa
 import tempfile
 import soundfile as sf
 
+
 class RealTimeTranslator:
     def __init__(self):
         # Initialize Whisper model for speech recognition
@@ -19,9 +20,6 @@ class RealTimeTranslator:
         self.device = "cuda" if torch.cuda.is_available() else "cpu"
         self.model = self.model.to(self.device)
 
-        # Initialize translator
-        self.translator = Translator()
-
         # Supported languages
         self.languages = {
             'en': 'English',
@@ -47,9 +45,12 @@ class RealTimeTranslator:
         return transcription[0]
 
     def translate_text(self, text, source_lang, target_lang):
-        """Translate text using Google Translate"""
-        translation = self.translator.translate(text, src=source_lang, dest=target_lang)
-        return translation.text
+        """Translate text using deep-translator"""
+        try:
+            translated_text = GoogleTranslator(source=source_lang, target=target_lang).translate(text)
+            return translated_text
+        except Exception as e:
+            return f"Translation error: {str(e)}"
 
     def text_to_speech(self, text, target_lang):
         """Convert text to speech using gTTS"""
@@ -90,6 +91,7 @@ class RealTimeTranslator:
         except Exception as e:
             return None, f"Error: {str(e)}", f"Error: {str(e)}"
 
+
 def create_gradio_interface():
     translator = RealTimeTranslator()
 
@@ -116,6 +118,7 @@ def create_gradio_interface():
     )
     return demo
 
+
 if __name__ == "__main__":
     demo = create_gradio_interface()
-    demo.launch(share=True, debug=True)
+    demo.launch(share=True, debug=True)