import torch
import gradio as gr
import requests
import os 
import transformers
from transformers import AutoModelWithLMHead, AutoTokenizer, AutoModelForCausalLM, pipeline
from transformers import GPT2Tokenizer, GPT2Model

tokenizer = AutoTokenizer.from_pretrained("samroni/puisi_model_gpt2_small")

model = AutoModelForCausalLM.from_pretrained("samroni/puisi_model_gpt2_small")
pipe = pipeline('text-generation', model="samroni/puisi_model_gpt2_small", tokenizer=tokenizer)


def text_generation(input_text, seed):
  input_ids = tokenizer(input_text, return_tensors="pt").input_ids
  torch.manual_seed(seed) # Max value: 18446744073709551615
  outputs = model.generate(input_ids, do_sample=True, max_length=100)
  generated_text = tokenizer.batch_decode(outputs, skip_special_tokens=True)
  return generated_text

title = "Indonesia Poem Generator Demo GPT2"
description = "Poem Generator "

gr.Interface(
    text_generation,
    [gr.inputs.Textbox(lines=2, label="Enter input text"), gr.inputs.Number(default=10, label="Enter seed number")],
    [gr.outputs.Textbox(type="auto", label="Text Generated")],
    title=title,
    description=description,
    theme="huggingface"
).launch()