from transformers import AutoTokenizer, AutoModelWithLMHead, TranslationPipeline, pipeline

model_checkpoint = "Helsinki-NLP/opus-mt-en-fr"
translator = pipeline("translation", model=model_checkpoint)
# print(translator("how old are you"))

########################################################################################

from transformers import AutoTokenizer, AutoModelWithLMHead, TranslationPipeline

pipeline = TranslationPipeline(
    model=AutoModelWithLMHead.from_pretrained("SEBIS/legal_t5_small_trans_fr_en"),
    tokenizer=AutoTokenizer.from_pretrained(pretrained_model_name_or_path =
        "SEBIS/legal_t5_small_trans_fr_en", do_lower_case=False, skip_special_tokens=True), device=0)

fr_text = "salut, comment vas-tu ?"

translator2 = pipeline([fr_text], max_length=512)

print(translator2)

########################################################################################
responseBase = "this is the second test"

def englishtofrench():
    print(translator(responseBase))
    return translator(responseBase)

englishtofrench()