import streamlit as st
import requests
from transformers import pipeline

# Set up the page
st.set_page_config(page_title="AI-Powered Language Learning Assistant", page_icon="🧠", layout="wide")

# Header and introduction
st.title("🧠 AI-Powered Language Learning Assistant")
st.markdown("""
Welcome to your AI-powered language assistant! Here you can:
- Translate words or sentences to different languages (using LibreTranslate API)
- Learn and practice new vocabulary
- Get grammar feedback.
""")

# Translation Function (Using LibreTranslate API)
def translate_text(text, target_language):
    url = "https://libretranslate.de/translate"  # Free LibreTranslate API
    payload = {
        'q': text,
        'source': 'en',
        'target': target_language
    }
    response = requests.post(url, data=payload)
    if response.status_code == 200:
        return response.json()['translatedText']
    else:
        return "Translation failed."

# Vocabulary Practice Section using Hugging Face's BERT Model
st.markdown("---")
st.header("Vocabulary Practice")
word_input = st.text_input("Enter a word to get its definition and synonyms", "")
if word_input:
    try:
        word_model = pipeline("fill-mask", model="bert-base-uncased")  # Using BERT to predict related words
        result = word_model(f"The synonym of {word_input} is [MASK].")
        st.write(f"Synonyms or related words for **{word_input}**: {result}")
    except Exception as e:
        st.error(f"Error fetching vocabulary practice data: {e}")

# Translation Section
st.markdown("---")
st.header("Translation")
text_input = st.text_input("Enter the text you want to translate", "")
language = st.selectbox("Select the language to translate to", ["es", "fr", "de", "it", "pt", "ru"])

if text_input:
    translated_text = translate_text(text_input, language)
    st.subheader(f"Translated Text to {language.upper()}:")
    st.write(translated_text)

# Footer for engagement
st.markdown("""
---
**Need more practice?** Visit [LibreTranslate API](https://libretranslate.de/) for real-time translations and Hugging Face for more language models!
""")