Create Example_Loader.py

Example_Loader.py

@@ -0,0 +1,141 @@
+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()