| import gradio as gr |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
|
|
| model_name = "sberbank-ai/rugpt3small_based_on_gpt2" |
| tokenizer = AutoTokenizer.from_pretrained(model_name) |
| model = AutoModelForCausalLM.from_pretrained(model_name) |
|
|
| chat_history = [] |
|
|
| def chat_with_ai(user_input): |
| global chat_history |
| context = " ".join(chat_history) + " " + user_input |
| inputs = tokenizer(context, return_tensors="pt") |
| outputs = model.generate(**inputs, max_length=200, pad_token_id=tokenizer.eos_token_id) |
| response = tokenizer.decode(outputs[0], skip_special_tokens=True) |
| |
| chat_history.append(f"Пользователь: {user_input}") |
| chat_history.append(f"ИИ: {response}") |
| return response |
|
|
| iface = gr.Interface( |
| fn=chat_with_ai, |
| inputs=gr.Textbox(lines=2, placeholder="Напиши что-нибудь..."), |
| outputs="text", |
| title="Русский чат-бот ИИ", |
| description="ИИ, который запоминает диалог и отвечает на русском" |
| ) |
|
|
| iface.launch() |
|
|
