Create LanguageTanslator.py

LanguageTanslator.py

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+import streamlit as st
+from transformers import MarianMTModel, MarianTokenizer
+
+def translate_text(text, src_lang, tgt_lang):
+    model_name = f'Helsinki-NLP/opus-mt-{src_lang}-{tgt_lang}'
+    model = MarianMTModel.from_pretrained(model_name)
+    tokenizer = MarianTokenizer.from_pretrained(model_name)
+    
+    translated = model.generate(**tokenizer(text, return_tensors="pt", padding=True))
+    translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
+    
+    return translated_text
+
+def main():
+    st.title("Language Translator App")
+    
+    # Language options
+    language_dict = {
+        "English": "en",
+        "French": "fr",
+        "German": "de",
+        "Spanish": "es",
+        "Italian": "it",
+        "Russian": "ru",
+        "Chinese": "zh",
+        "Japanese": "ja",
+        "Korean": "ko",
+        "Arabic": "ar",
+    }
+    
+    src_lang = st.selectbox("Select Source Language", list(language_dict.keys()))
+    tgt_lang = st.selectbox("Select Target Language", list(language_dict.keys()))
+    
+    # Text input
+    text = st.text_area("Enter Text to Translate")
+    
+    # Translate button
+    if st.button("Translate"):
+        if text:
+            translated_text = translate_text(text, language_dict[src_lang], language_dict[tgt_lang])
+            st.write("Translated Text:")
+            st.success(translated_text)
+        else:
+            st.warning("Please enter text to translate.")
+
+if __name__ == "__main__":
+    main()
+