from transformers import MarianMTModel, MarianTokenizer

# Define the model names for different language pairs
model_names = {
'fr': 'Helsinki-NLP/opus-mt-en-fr',
'de': 'Helsinki-NLP/opus-mt-en-de',
'es': 'Helsinki-NLP/opus-mt-en-es',
'ja': 'Helsinki-NLP/opus-mt-en-ja'
}

# Function to translate text into multiple languages
def translate_to_multiple_languages(text, src_lang='en', target_langs=['fr', 'de', 'es', 'ja']):
translations = {}
for tgt_lang in target_langs:
model_name = model_names.get(tgt_lang)
if model_name:
model = MarianMTModel.from_pretrained(model_name)
tokenizer = MarianTokenizer.from_pretrained(model_name)
translated = model.generate(**tokenizer(text, return_tensors="pt", padding=True))
translated_text = [tokenizer.decode(t, skip_special_tokens=True) for t in translated]
translations[tgt_lang] = translated_text[0]
return translations

# Example usage
text = "Hello, how are you?"

# Translate to multiple languages
translations = translate_to_multiple_languages(text)
for lang, translation in translations.items():
print(f"Translation to {lang}: {translation}")