Update app.py

app.py

@@ -1,42 +1,40 @@
 import streamlit as st
 from transformers import pipeline
 
-# Load the translation pipeline from Hugging Face
-@st.cache_resource
-def load_translation_pipeline(model_name):
-    return pipeline("translation", model=model_name)
-
-# Dictionary of available models and target languages
-models = {
+# Define model mapping for each target language
+model_mapping = {
     "French": "Helsinki-NLP/opus-mt-en-fr",
     "Spanish": "Helsinki-NLP/opus-mt-en-es",
     "German": "Helsinki-NLP/opus-mt-en-de",
-    "Chinese": "Helsinki-NLP/opus-mt-en-zh",
-    "Hindi": "Helsinki-NLP/opus-mt-en-hi",
+    "Italian": "Helsinki-NLP/opus-mt-en-it",
+    "Urdu": "Helsinki-NLP/opus-mt-en-ur"  # Added Urdu translation
 }
 
 # Streamlit app
-def main():
-    st.title("Language Translator")
-
-    # Input text from the user
-    text_to_translate = st.text_area("Enter the text in English:")
-
-    # Select the target language
-    target_language = st.selectbox("Select the target language:", list(models.keys()))
-
-    # Translate button
+st.title("Language Translator")
+
+# Sidebar for language selection and translation output
+with st.sidebar:
+    st.header("Translate Text")
+    
+    # Input text
+    text = st.text_area("Enter text in English:")
+    
+    # Target language selection
+    selected_language = st.selectbox("Select target language:", list(model_mapping.keys()))
+    
+    # Translation button
     if st.button("Translate"):
-        # Load the appropriate translation model
-        translation_pipeline = load_translation_pipeline(models[target_language])
-
-        # Translate the text
-        if text_to_translate.strip():
-            translated_text = translation_pipeline(text_to_translate)[0]['translation_text']
-            st.success(f"Translated Text ({target_language}):")
-            st.write(translated_text)
+        if text:
+            # Get the appropriate model based on selected language
+            model_name = model_mapping[selected_language]
+            translator = pipeline("translation", model=model_name)
+            
+            # Perform translation
+            translation = translator(text, max_length=400)[0]['translation_text']
+            
+            # Display translation
+            st.write(f"*Translation in {selected_language}:*")
+            st.write(translation)
         else:
-            st.error("Please enter some text to translate.")
-
-if __name__ == "__main__":
-    main()
+            st.write("Please enter some text to translate.")