import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import nltk
nltk.download('punkt')

def generate_answer(question):
  model_name = "anukvma/bart-aiml-question-answer-v2"
  tokenizer = AutoTokenizer.from_pretrained(model_name)
  model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
  inputs = ["Answer this AIML Question: " + question]
  inputs = tokenizer(inputs, max_length=256, truncation=True, return_tensors="pt")
  output = model.generate(**inputs, num_beams=8, do_sample=True, min_length=1, max_length=512)
  decoded_output = tokenizer.batch_decode(output, skip_special_tokens=True)[0]
  predicted_title = nltk.sent_tokenize(decoded_output.strip())[0]
  return predicted_title


iface = gr.Interface(
    fn=generate_answer,
    inputs=[
        gr.Textbox(lines=5, label="Question")
    ],
    outputs=gr.Textbox(label="Answer")
)

iface.launch()