import torch
import transformers
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import gradio as gr

tokenizer = AutoTokenizer.from_pretrained("AhmedSSoliman/MarianCG_NL2Code")
model = AutoModelForSeq2SeqLM.from_pretrained("AhmedSSoliman/MarianCG_NL2Code")

def generate_code(NL):
    inputs = tokenizer([NL], padding="max_length", truncation=True, max_length=512, return_tensors="pt")
    input_ids = inputs.input_ids.to("cuda")
    attention_mask = inputs.attention_mask.to("cuda")
    outputs = new_model.generate(input_ids, attention_mask=attention_mask)
    # all special tokens including will be removed
    output_code = tokenizer.batch_decode(outputs, skip_special_tokens=True)
    return output_code
    

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

#output_text = gr.outputs.Textbox()
#gr.Interface(generate_code,"textbox", output_text, title="MarianMT Code Generation", description="MarianMT Code Generation").launch()