import gradio as gr
import subprocess

subprocess.check_call(["pip", "install", "transformers"])
subprocess.check_call(["pip", "install", "torch"])


from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("balaramas/mbart-enhiriser")
model = AutoModelForSeq2SeqLM.from_pretrained("balaramas/mbart-enhiriser")

def greet(ar_en):
    tokenizer.src_lang = "en_XX"
    encoded_ar = tokenizer(ar_en, return_tensors="pt")
    generated_tokens = model.generate(
        **encoded_ar,
        forced_bos_token_id=tokenizer.lang_code_to_id["hi_IN"]
    )
    output = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)

    
    return output

iface = gr.Interface(fn=greet, inputs="text", outputs="text")
iface.launch()