| import gradio as gr | |
| from transformers import pipeline | |
| # Modello più piccolo e CPU esplicita | |
| generator = pipeline("text-generation", model="sshleifer/tiny-gpt2", device="cpu") | |
| def chat_function(message, history): | |
| response = generator(message, max_length=50, num_return_sequences=1)[0]["generated_text"] | |
| return history + [{"role": "user", "content": message}, {"role": "assistant", "content": response}] | |
| interface = gr.ChatInterface( | |
| fn=chat_function, | |
| chatbot=gr.Chatbot(type="messages"), | |
| title="Chatbot IA" | |
| ) | |
| interface.launch() |