| import gradio as gr | |
| from transformers import pipeline | |
| import torch | |
| # Cek GPU | |
| device = 0 if torch.cuda.is_available() else -1 | |
| # Load model (akan otomatis download pertama kali) | |
| print("Loading AI model...") | |
| generator = pipeline( | |
| 'text-generation', | |
| model='microsoft/DialoGPT-small', # Model kecil, cepat | |
| device=device | |
| ) | |
| def chat(message, history): | |
| # Build context | |
| context = "" | |
| for h in history[-3:]: | |
| context += f"User: {h[0]}\nAI: {h[1]}\n" | |
| prompt = f"{context}User: {message}\nAI:" | |
| # Generate response | |
| result = generator( | |
| prompt, | |
| max_length=150, | |
| temperature=0.8, | |
| do_sample=True, | |
| pad_token_id=50256 | |
| ) | |
| response = result[0]['generated_text'] | |
| response = response.replace(prompt, "").strip() | |
| if not response: | |
| response = "Maaf kak, saya kurang paham. Bisa diulang? 😊" | |
| history.append((message, response)) | |
| return history, history | |
| # UI | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# 🤖 Bangdim AI") | |
| chatbot = gr.Chatbot() | |
| msg = gr.Textbox(label="Pesan") | |
| clear = gr.Button("Clear") | |
| msg.submit(chat, [msg, chatbot], [chatbot, msg]) | |
| clear.click(lambda: None, None, chatbot) | |
| demo.launch() |