app.py

import gradio as gr
import os 
os.system('pip install transformers torch')
from transformers import GPT2LMHeadModel, GPT2Tokenizer

# Load the pre-trained model and tokenizer
model_name = "microsoft/DialoGPT-small"
model = GPT2LMHeadModel.from_pretrained(model_name)
tokenizer = GPT2Tokenizer.from_pretrained(model_name)

def generate_response(prompt, max_length=50, temperature=0.8):
    input_ids = tokenizer.encode(prompt, return_tensors="pt")
    output_ids = model.generate(input_ids, max_length=max_length, temperature=temperature, num_return_sequences=1)
    response = tokenizer.decode(output_ids[0], skip_special_tokens=True)
    return response

iface = gr.Interface(
    fn=generate_response,
    inputs=gr.Textbox(),
    outputs="text",
    capture_session=True
)

iface.launch()