Update app.py

app.py

@@ -1,9 +1,8 @@
 import streamlit as st
 from transformers import T5ForConditionalGeneration, T5Tokenizer
 from googletrans import Translator
-from gtts import gTTS  # Google Text-to-Speech
-import pyttsx3
-import time
+from gtts import gTTS
+import asyncio  # Add asyncio
 import os
 
 # Set up Streamlit page
@@ -16,76 +15,63 @@ st.markdown("Enter text in English, and we'll create a **fusion** of multiple la
 translator = Translator()
 
 # Load T5 model
-model_name = "t5-small"  # Can be changed to a larger model
+model_name = "t5-small"
 model = T5ForConditionalGeneration.from_pretrained(model_name)
 tokenizer = T5Tokenizer.from_pretrained(model_name)
 
-# Language codes for translation
+# Language codes
 languages = {
     'es': 'Spanish', 'fr': 'French', 'de': 'German', 'it': 'Italian', 'zh-cn': 'Chinese',
     'ja': 'Japanese', 'hi': 'Hindi', 'ar': 'Arabic', 'mr': 'Marathi', 'ta': 'Tamil',
     'el': 'Greek', 'la': 'Latin', 'pl': 'Polish', 'ru': 'Russian', 'tr': 'Turkish'
 }
 
-# Function to generate multilingual fusion text
+# Function to mix languages using T5 model
 def mix_languages_with_model(text):
     input_text = f"Translate to mixed languages: {text}"
     inputs = tokenizer.encode(input_text, return_tensors="pt", max_length=512, truncation=True)
-    
-    # Generate fusion text
     outputs = model.generate(inputs, max_length=100, num_beams=5, early_stopping=True)
     mixed_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    
     return mixed_text
 
-# Function to translate text into multiple languages
-def translate_text(text):
+# ✅ ASYNC FIX: Translate text properly
+async def translate_text(text):
     translations = {}
     for code, lang in languages.items():
         try:
-            translated_text = translator.translate(text, dest=code).text
-            translations[lang] = translated_text
+            translation = await translator.translate(text, dest=code)
+            translations[lang] = translation.text  # ✅ FIXED: `await` required
         except Exception as e:
             translations[lang] = f"Translation failed: {str(e)}"
     return translations
 
-# Function to convert text to speech using Google TTS (fallback to pyttsx3)
+# Function to convert text to speech
 def text_to_speech(text):
     try:
-        time.sleep(2)  # Prevent API rate limits
         tts = gTTS(text=text, lang="en")
         tts.save("output.mp3")
         return "output.mp3"
     except Exception as e:
-        st.warning(f"Google TTS failed: {e}. Trying local TTS...")
-        
-        # Try local TTS
-        try:
-            engine = pyttsx3.init()
-            engine.save_to_file(text, "output.mp3")
-            engine.runAndWait()
-            return "output.mp3"
-        except Exception as e:
-            st.error(f"Local TTS also failed: {e}")
-            return None
+        st.error(f"Google TTS failed: {e}")
+        return None
 
-# Streamlit user input
+# User input
 input_text = st.text_area("📝 Enter your text in English:")
 
 if st.button("Generate Fusion Language"):
     if input_text:
-        # Generate fusion text
+        # Generate mixed language text
         fused_text = mix_languages_with_model(input_text)
         st.subheader("🌐 Generated Fusion Language:")
         st.write(fused_text)
 
-        # Convert fusion text to speech
+        # Convert to speech
         audio_file = text_to_speech(fused_text)
         if audio_file:
-            st.audio(audio_file, format='audio/mp3')  # ✅ FIXED: Removed use_column_width=True
+            st.audio(audio_file, format='audio/mp3')
 
-        # Translate fusion text into multiple languages
-        translations = translate_text(fused_text)
+        # ✅ Fix translation call with `asyncio.run()`
+        translations = asyncio.run(translate_text(fused_text))
         st.subheader("🗣️ Translations in Different Languages:")
         for lang, translation in translations.items():
             st.write(f"**{lang}:** {translation}")