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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()
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