import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, AutoModelForCausalLM
tokenizer1 = AutoTokenizer.from_pretrained("salesken/translation-hi-en")
model1 = AutoModelForSeq2SeqLM.from_pretrained("salesken/translation-hi-en")
#tokenizer = AutoTokenizer.from_pretrained("Salesforce/codegen-16B-mono")
#model = AutoModelForCausalLM.from_pretrained("Salesforce/codegen-16B-mono")

def greet(name):
    hin_snippet = name
    inputs = tokenizer1.encode(hin_snippet, return_tensors="pt",padding=True,max_length=512,truncation=True)
    outputs = model1.generate(inputs, max_length=128, num_beams=None, early_stopping=True)
    translated = tokenizer1.decode(outputs[0]).replace('<pad>',"").strip().lower()
    #input_ids = tokenizer("# "+name, return_tensors="pt").input_ids
    #sample1 = model.generate(input_ids, max_length=128)
    #return tokenizer.decode(sample1[0], skip_special_tokens=True)
    return translated

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