app.py

# 📦 Install required libraries first (in your Hugging Face Space or Colab, use !pip install ...)
# !pip install transformers sentencepiece

from transformers import pipeline

def main():
    # ✅ Create translation pipeline for t5-small (English → German)
    t5_translator = pipeline("translation_en_to_de", model="t5-small")

    # ✅ Create translation pipeline for Helsinki-NLP/opus-mt-en-ta (English → Tamil)
    ta_translator = pipeline("translation_en_to_ta", model="Helsinki-NLP/opus-mt-en-ta")

    # Example text to translate
    text_en1 = "This is a simple text to translate."
    text_en2 = "Nature is beautiful and full of wonders."

    # Translate using t5-small
    result_t5 = t5_translator(text_en1, max_length=40)
    print("🔹 T5-small translation (English → German):")
    print(result_t5[0]['translation_text'])

    print()  # blank line

    # Translate using Helsinki-NLP/opus-mt-en-ta
    result_ta = ta_translator(text_en2, max_length=40)
    print("🔹 Helsinki-NLP English → Tamil translation:")
    print(result_ta[0]['translation_text'])


if __name__ == "__main__":
    main()