import streamlit as st
from transformers import pipeline

# Title and description
st.title("Language Translator")
st.markdown("Translate text from English to Spanish using the Hugging Face model `Helsinki-NLP/opus-mt-en-es`.")

# Load the translation pipeline
@st.cache_resource
def load_translator():
    return pipeline("translation_en_to_es", model="Helsinki-NLP/opus-mt-en-es")

translator = load_translator()

# Input area for English text
user_input = st.text_area("Enter text in English:", placeholder="Type something in English...", height=200)

# Translate button
if st.button("Translate"):
    if user_input.strip():
        with st.spinner("Translating text..."):
            # Perform translation
            translated = translator(user_input, max_length=100)
            translated_text = translated[0]["translation_text"]

        # Display the translated text
        st.markdown("### Translated Text:")
        st.write(translated_text)
    else:
        st.warning("Please enter some text to translate.")

# Footer
st.markdown("---")
st.markdown("Powered by [Hugging Face Transformers](https://huggingface.co/transformers/) and Streamlit.")