Example_Loader.py

import torch
import torch.nn as nn
import json
import random
from collections import deque

# ============ КЛАСС МОДЕЛИ (ДОЛЖЕН СОВПАДАТЬ) ============
class AndreyBot(nn.Module):
    def __init__(self, vocab_size=89, hidden_size=256, num_layers=2, embedding_dim=64):
        super().__init__()
        self.vocab_size = vocab_size
        self.hidden_size = hidden_size
        self.num_layers = num_layers
        self.embedding_dim = embedding_dim
        self.embedding = nn.Embedding(vocab_size, embedding_dim)
        self.lstm = nn.LSTM(embedding_dim, hidden_size, batch_first=True, num_layers=num_layers, dropout=0.2)
        self.fc = nn.Linear(hidden_size, vocab_size)
        self.dropout = nn.Dropout(0.2)
        
    def forward(self, x):
        if x.dim() == 1:
            x = x.unsqueeze(0)
        emb = self.embedding(x)
        out, _ = self.lstm(emb)
        out = self.dropout(out)
        out = out[:, -1, :]
        return self.fc(out)

# ============ ЗАГРУЗЧИК ============
class AndreyLoader:
    def __init__(self, model_path='andrey_full.pt'):
        print("🤖 Загрузка Андрея...")
        
        # Загружаем чекпоинт
        checkpoint = torch.load(model_path, map_location='cpu')
        
        # Создаём модель
        self.model = AndreyBot(
            vocab_size=checkpoint['vocab_size'],
            hidden_size=checkpoint['hidden_size'],
            num_layers=checkpoint['num_layers'],
            embedding_dim=checkpoint['embedding_dim']
        )
        self.model.load_state_dict(checkpoint['model_state_dict'])
        self.model.eval()
        
        # Загружаем словари
        self.word_to_idx = checkpoint['word_to_idx']
        self.idx_to_word = {int(k): v for k, v in checkpoint['idx_to_word'].items()}
        
        # Параметры
        self.vocab_size = checkpoint['vocab_size']
        self.epoch = checkpoint['epoch']
        
        # Константы
        self.PAD = 0
        self.UNK = 1
        
        print(f"✅ Андрей загружен!")
        print(f"   📚 Словарь: {self.vocab_size} слов")
        print(f"   🧠 Обучен: {self.epoch} эпох")
    
    def tokenize(self, text):
        """Текст → список токенов"""
        words = text.lower().split()
        return [self.word_to_idx.get(w, self.UNK) for w in words if w in self.word_to_idx]
    
    def detokenize(self, tokens):
        """Токены → текст"""
        words = []
        for t in tokens:
            if t not in [self.PAD, self.UNK]:
                words.append(self.idx_to_word.get(t, '?'))
        return ' '.join(words)
    
    def generate(self, question, temperature=0.85, max_length=12):
        """Генерация ответа"""
        tokens = self.tokenize(question)
        
        if not tokens:
            return "..."
        
        current = tokens[0]
        response_tokens = []
        
        with torch.no_grad():
            for _ in range(max_length):
                # Получаем логиты от модели
                logits = self.model(torch.tensor([[current]]))
                
                # Применяем температуру
                probs = torch.softmax(logits[0] / temperature, dim=-1)
                
                # Top-K выбор
                top_k = min(5, self.vocab_size)
                top_probs, top_idx = torch.topk(probs, top_k)
                probs = top_probs / top_probs.sum()
                current = top_idx[torch.multinomial(probs, 1)].item()
                
                # Пропускаем спецтокены
                if current in [self.PAD, self.UNK]:
                    continue
                
                response_tokens.append(current)
                
                # Останавливаемся при длине
                if len(response_tokens) >= max_length - 2:
                    break
        
        if not response_tokens:
            return "..."
        
        return self.detokenize(response_tokens)
    
    def chat(self):
        """Запуск чата"""
        print("\n" + "="*50)
        print("🤖 АНДРЕЙ")
        print("   Скажи 'пока' для выхода")
        print("="*50 + "\n")
        
        while True:
            user = input("👤 Вы: ").strip().lower()
            
            if user in ['пока', 'выход', 'exit', 'quit']:
                print("🤖 Андрей: Пока! 👋")
                break
            
            if user == '':
                continue
            
            answer = self.generate(user)
            print(f"🤖 Андрей: {answer}\n")

# ============ ЗАПУСК ============
if __name__ == "__main__":
    # Загружаем Андрея
    andrey = AndreyLoader('andrey_full.pt')
    
    # Запускаем чат
    andrey.chat()