app.py

import streamlit as st
from transformers import pipeline

# Function to load translation pipeline
@st.cache_resource
def load_translator(target_language):
    model_name = f"Helsinki-NLP/opus-mt-en-{target_language}"
    return pipeline("translation", model=model_name)

# Supported languages
supported_languages = {
    "fr": "French",
    "es": "Spanish",
    "de": "German",
    "zh": "Chinese",
    "hi": "Hindi",
    "ar": "Arabic",
    "ru": "Russian",
    "ja": "Japanese",
    "ko": "Korean",
    "it": "Italian",
}

# Streamlit App
st.title("🌍 Language Translator App")
st.write("Translate text from English to any supported language using Hugging Face models.")

# User input for text
input_text = st.text_area("Enter text in English:", placeholder="Type here...")

# Dropdown to select target language
target_language = st.selectbox(
    "Select target language:",
    options=list(supported_languages.keys()),
    format_func=lambda lang: f"{supported_languages[lang]} ({lang})",
)

# Translate button
if st.button("Translate"):
    if not input_text.strip():
        st.error("❌ Please enter some text to translate.")
    else:
        try:
            st.info("⏳ Translating...")
            translator = load_translator(target_language)
            translation = translator(input_text)[0]["translation_text"]
            st.success("✅ Translated Text:")
            st.write(translation)
        except Exception as e:
            st.error(f"⚠️ An error occurred: {str(e)}")