Update app.py

app.py

@@ -1,50 +1,50 @@
 import streamlit as st
-from transformers import MarianMTModel, MarianTokenizer
-
-# Define a dictionary to map language names to model identifiers
-models = {
-    'French': 'Helsinki-NLP/opus-mt-en-fr',
-    'Spanish': 'Helsinki-NLP/opus-mt-en-es',
-    'German': 'Helsinki-NLP/opus-mt-en-de',
-    'Italian': 'Helsinki-NLP/opus-mt-en-it',
-    'Urdu': 'Helsinki-NLP/opus-mt-en-ur',
-    'Arabic': 'Helsinki-NLP/opus-mt-en-ar', 
-    # Add more language models if needed
-}
-
-def load_model(model_name):
-    """Load the model and tokenizer based on the selected model name."""
-    model = MarianMTModel.from_pretrained(model_name)
-    tokenizer = MarianTokenizer.from_pretrained(model_name)
-    return model, tokenizer
-
-def translate_text(text, model, tokenizer):
-    """Translate text using the provided model and tokenizer."""
-    inputs = tokenizer.encode(text, return_tensors="pt")
-    translated = model.generate(inputs)
-    translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
-    return translated_text
-
-def main():
-    st.title("Multilingual Translator")
-
-    # User input for English text
-    text_to_translate = st.text_area("Enter text in English:")
-
-    # Language options
-    selected_language = st.selectbox("Select target language:", list(models.keys()))
-
-    if st.button("Translate"):
-        if text_to_translate:
-            # Load the selected model
-            model_name = models[selected_language]
-            model, tokenizer = load_model(model_name)
-            
-            translated_text = translate_text(text_to_translate, model, tokenizer)
-            st.write(f"**Translation in {selected_language}:**")
-            st.write(translated_text)
-        else:
-            st.warning("Please enter text to translate.")
-
-if __name__ == "__main__":
-    main()
+	from transformers import MarianMTModel, MarianTokenizer
+	
+	# Define a dictionary to map language names to model identifiers
+	models = {
+	    'French': 'Helsinki-NLP/opus-mt-en-fr',
+	    'Spanish': 'Helsinki-NLP/opus-mt-en-es',
+	    'German': 'Helsinki-NLP/opus-mt-en-de',
+	    'Italian': 'Helsinki-NLP/opus-mt-en-it',
+	    'Urdu': 'Helsinki-NLP/opus-mt-en-ur',
+	    'Arabic': 'Helsinki-NLP/opus-mt-en-ar', 
+	    # Add more language models if needed
+	}
+	
+	def load_model(model_name):
+	    """Load the model and tokenizer based on the selected model name."""
+	    model = MarianMTModel.from_pretrained(model_name)
+	    tokenizer = MarianTokenizer.from_pretrained(model_name)
+	    return model, tokenizer
+	
+	def translate_text(text, model, tokenizer):
+	    """Translate text using the provided model and tokenizer."""
+	    inputs = tokenizer.encode(text, return_tensors="pt")
+	    translated = model.generate(inputs)
+	    translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
+	    return translated_text
+	
+	def main():
+	    st.title("Multilingual Translator")
+	
+	    # User input for English text
+	    text_to_translate = st.text_area("Enter text in English:")
+	
+	    # Language options
+	    selected_language = st.selectbox("Select target language:", list(models.keys()))
+	
+	    if st.button("Translate"):
+	        if text_to_translate:
+	            # Load the selected model
+	            model_name = models[selected_language]
+	            model, tokenizer = load_model(model_name)
+	            
+	            translated_text = translate_text(text_to_translate, model, tokenizer)
+	            st.write(f"**Translation in {selected_language}:**")
+	            st.write(translated_text)
+	        else:
+	            st.warning("Please enter text to translate.")
+	
+	if __name__ == "__main__":
+	    main()