app.py

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

# Load the pre-trained GPT-2 model and tokenizer
tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
model = TFGPT2LMHeadModel.from_pretrained("gpt2", pad_token_id=tokenizer.eos_token_id)

# Define a function for generating responses
def chatbot(input_text):
    # Tokenize the input text
    input_ids = tokenizer.encode(input_text, return_tensors="tf")

    # Generate a response from the model
    output_ids = model.generate(input_ids, max_length=100, pad_token_id=tokenizer.eos_token_id)

    # Decode the response and return it
    response_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
    return response_text

# Create a Gradio interface for the chatbot
gr.Interface(
    fn=chatbot,
    inputs="text",
    outputs="text",
    title="GPT-2 Chatbot",
    description="Ask me anything!"
).launch()