| import streamlit as st | |
| from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM | |
| translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-ru") | |
| def translate_text(text): | |
| if text: | |
| result = translator(text) | |
| return result[0]['translation_text'] | |
| return "" | |
| st.title("Text Translation App") | |
| st.subheader("Enter text to translate:") | |
| user_input = st.text_area("Your text here:", height=200) | |
| if st.button("Translate"): | |
| translation = translate_text(user_input) | |
| st.subheader("Translated Text:") | |
| st.write(translation) | |
| else: | |
| st.info("Enter text and click 'Translate' to see the result.") | |
| if __name__ == '__main__': | |
| import streamlit.web.cli as stcli | |
| stcli.main() | |