app.py

import gradio as gr
from transformers import GPT2LMHeadModel, GPT2Tokenizer
import random

# Загрузка модели и токенизатора
model_name = "ai-forever/rugpt3large_based_on_gpt2"
tokenizer = GPT2Tokenizer.from_pretrained(model_name)
model = GPT2LMHeadModel.from_pretrained(model_name)

# Загрузка случайных фраз из файла dialogues.txt
with open("dialogues.txt", "r", encoding="utf-8") as file:
    random_phrases = [line.strip() for line in file.readlines() if line.strip()]

# Функция генерации ответа
def generate(prompt, _=None):
    random_phrase = random.choice(random_phrases)
    user_input = f"[USER]: {prompt}\n[BOT]: "
    inputs = tokenizer.encode(user_input, return_tensors="pt")
    outputs = model.generate(inputs, max_length=25, num_return_sequences=1, pad_token_id=tokenizer.eos_token_id)
    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
    edit_response = response.split(f"[BOT]: ")[-1].strip()
    if "[" in edit_response:
      edit_response = edit_response.split("[")[0]
    bot_message = f"[BOT!]: {edit_response}"
    return bot_message

# Настройка интерфейса чат-бота
mychatbot = gr.Chatbot(
    avatar_images=["./user.png", "./botm.png"], bubble_full_width=False, show_label=False, show_copy_button=True, likeable=True
)

# Создание интерфейса для чат-бота
demo = gr.ChatInterface(
    fn=generate,
    chatbot=mychatbot,
    title="🤬НЕАДЕКВАТ🤬",
    retry_btn=None,
    undo_btn=None
)

if __name__ == "__main__":
    demo.launch(share=True)