Update app.py

app.py

@@ -1,14 +1,70 @@
+!pip install transformers
+from transformers import GPTJForCausalLM, GPT2Tokenizer
+import torch
+
+
+# Загрузка токенизатора и модели
+tokenizer = GPT2Tokenizer.from_pretrained("EleutherAI/gpt-j-6B")
+model = GPTJForCausalLM.from_pretrained("EleutherAI/gpt-j-6B")
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model = model.to(device)
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model = model.to(device)
+from transformers import MarianMTModel, MarianTokenizer
+# Функции для перевода
+def translate_to_english(text):
+    tokenizer = MarianTokenizer.from_pretrained("Helsinki-NLP/opus-mt-ru-en")
+    model = MarianMTModel.from_pretrained("Helsinki-NLP/opus-mt-ru-en")
+    translated = model.generate(**tokenizer.prepare_seq2seq_batch([text], return_tensors="pt"))
+    return tokenizer.decode(translated[0])
+
+def translate_to_russian(text):
+    tokenizer = MarianTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-ru")
+    model = MarianMTModel.from_pretrained("Helsinki-NLP/opus-mt-en-ru")
+    translated = model.generate(**tokenizer.prepare_seq2seq_batch([text], return_tensors="pt"))
+    return tokenizer.decode(translated[0])
+
+def generate_response(input_text):
+    # Кодирование входного текста и генерация ответа
+    input_ids = tokenizer.encode(input_text, return_tensors='pt')
+    output = model.generate(input_ids, max_length=1500, num_return_sequences=1, pad_token_id=50256, 
+                            num_beams=5, early_stopping=True)
+
+    # Декодирование и возвращение ответа
+    response = tokenizer.decode(output[0], skip_special_tokens=True)
+    return response
+
+# Тестирование функции
+input_text = "What is the capital of France?"
+response = generate_response(input_text)
+print(response)
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model = model.to(device)
+user_input = ""
+while user_input.lower() != 'exit':
+    user_input = input("You: ")
+    if user_input.lower() != 'exit':
+        user_input_english = translate_to_english(user_input)
+        response_english = generate_response(user_input_english)
+        response_russian = translate_to_russian(response_english)
+        print(f"Bot: {response_russian}")
+
+
+
+! pip install --upgrade gradio -qq
 import gradio as gr
 
 def predict(message, history):
-    # output = message # debug mode
-
-    output = str(llm_ans(message))
-    return output
+    user_input_english = translate_to_english(message)
+    response_english = generate_response(user_input_english)
+    response_russian = translate_to_russian(response_english)
+    return response_russian
 
 demo = gr.ChatInterface(
     predict,
-    title = f'LLM ({CFG.model_name}) for MyChatENRU'
+    title='LLM for MyChatENRU'
 )
 
-demo.launch()
+demo.launch()