import gradio as gr
import tensorflow
from transformers import TFGPT2LMHeadModel, GPT2Tokenizer

tokenizer = GPT2Tokenizer.from_pretrained("gpt2")

model = TFGPT2LMHeadModel.from_pretrained("gpt2",pad_token_id=tokenizer.eos_token_id)

def generate_text(inp):
    input_ids = tokenizer.encode(inp, return_tensors='tf')
    beam_output = model.generate(input_ids, max_length=109, num_beams=5, no_repeat_ngram_size=2, early_stopping=True)

    output = tokenizer.decode(beam_output[0], skip_special_tokens=True, clean_up_tokenization_spaces=True)

    return ".".join(output.split(".")[:-1]) + "."
output_text = gr.outputs.Textbox()
gr.Interface(generate_text,"textbox",output_text, title="MAX-GPT",description = "Chat and ask about anything, leave unfinished sentences for autocomplete or just ask questions revolving any topic").launch(share=True)