Update app.py

app.py

@@ -1,53 +1,50 @@
-
-try:
-    from transformers import MarianMTModel, MarianTokenizer
-    print("Transformers imported successfully")
-except ImportError as e:
-    print(f"ImportError: {e}")
-
 import streamlit as st
-
-# Attempt to import the transformers package
-try:
-    from transformers import MarianMTModel, MarianTokenizer
-except ImportError as e:
-    st.error("Failed to import transformers. Please make sure it is installed.")
-    st.stop()
-
-# Initialize the model and tokenizer
-def load_model_and_tokenizer(target_lang):
-    model_name = f'Helsinki-NLP/opus-mt-en-{target_lang}'
+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
 
-# Function to translate text
 def translate_text(text, model, tokenizer):
-    tokens = tokenizer(text, return_tensors="pt", padding=True)
-    translated_tokens = model.generate(**tokens)
-    translated_text = tokenizer.decode(translated_tokens[0], skip_special_tokens=True)
+    """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
 
-# Streamlit app
-st.title("Language Translator")
+def main():
+    st.title("Multilingual Translator")
 
-# Input text
-input_text = st.text_area("Enter text to translate", "Hello, how are you?")
+    # User input for English text
+    text_to_translate = st.text_area("Enter text in English:")
 
-# Language selection
-target_language = st.selectbox(
-    "Select target language",
-    ["fr", "de", "es", "it", "pt", "ru", "zh", "ja", "ar"]
-)
+    # Language options
+    selected_language = st.selectbox("Select target language:", list(models.keys()))
 
-# Load model and tokenizer based on selected language
-if target_language:
-    model, tokenizer = load_model_and_tokenizer(target_language)
-    
     if st.button("Translate"):
-        if input_text:
-            translated_text = translate_text(input_text, model, tokenizer)
-            st.subheader("Translated text")
+        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.error("Please enter some text to translate.")
+            st.warning("Please enter text to translate.")
+
+if __name__ == "__main__":
+    main()