app.py

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

tokenizer = AutoTokenizer.from_pretrained("openai-gpt")
model = OpenAIGPTLMHeadModel.from_pretrained("openai-gpt")

def generate_response(text):
    inputs = tokenizer(text, return_tensors="pt")
    outputs = model(**inputs, labels=inputs["input_ids"])
    generated_ids = model.generate(inputs['input_ids'], 
                                   num_return_sequences=1,
                                   max_length=50)
    generated_text = tokenizer.decode(generated_ids.squeeze(), skip_special_tokens=True)
    return generated_text

iface = gr.Interface(
    fn=generate_response,
    inputs="text",
    outputs="text",
    title="OpenAI GPT4 Chatbot",
    description="Enter some text, and the OpenAI GPT model will generate a response.",
    examples=[
        ["Hello, how are you?"],
        ["What is the capital of France?"],
        ["Tell me a joke."]
    ]
)

iface.launch()