Update app.py

app.py

@@ -1,23 +1,31 @@
 import gradio as gr
 from transformers import pipeline, AutoTokenizer, logging
-import threading, torch, warnings
 from langdetect import detect
+import threading, warnings, os, torch
 
-# --- Disable warnings and logs ---
+# --- Silent mode ---
+os.environ["TOKENIZERS_PARALLELISM"] = "false"
+os.environ["TRANSFORMERS_NO_ADVISORY_WARNINGS"] = "1"
 warnings.filterwarnings("ignore")
 logging.set_verbosity_error()
 
+# --- Global vars ---
 models = {}
 models_ready = False
 status_message = "⏳ Инициализация моделей (1–2 мин)..."
 
+# --- Model loader ---
 def load_model(model_name, task="summarization"):
-    """Безопасная загрузка с fallback на legacy-токенайзер и half precision"""
     try:
         print(f"🔄 Загружается модель: {model_name}")
-        tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=False, legacy=True)
+        tokenizer = AutoTokenizer.from_pretrained(
+            model_name,
+            use_fast=False,
+            legacy=True,
+            trust_remote_code=True
+        )
         model_pipe = pipeline(task, model=model_name, tokenizer=tokenizer, device=-1)
-        # Оптимизация PyTorch
+        # Torch optimizations
         if hasattr(model_pipe.model, "half"):
             model_pipe.model = model_pipe.model.half()
         if hasattr(torch, "compile"):
@@ -27,9 +35,10 @@ def load_model(model_name, task="summarization"):
                 pass
         return model_pipe
     except Exception as e:
-        print(f"⚠️ Ошибка загрузки {model_name}: {e}")
+        print(f"⚠️ Ошибка при загрузке {model_name}: {e}")
         return None
 
+# --- Preload all models asynchronously ---
 def preload_models():
     global models, models_ready, status_message
     try:
@@ -40,12 +49,12 @@ def preload_models():
         status_message = "✅ Все модели успешно загружены и оптимизированы!"
         print(status_message)
     except Exception as e:
-        status_message = f"❌ Ошибка при инициализации моделей: {e}"
+        status_message = f"❌ Ошибка инициализации моделей: {e}"
         print(status_message)
 
-# --- Lazy background loading ---
 threading.Thread(target=preload_models, daemon=True).start()
 
+# --- Summarization logic ---
 def summarize_text(text):
     if not text.strip():
         return "⚠️ Введите текст для суммаризации."
@@ -63,8 +72,12 @@ def summarize_text(text):
     except Exception as e:
         return f"⚠️ Ошибка суммаризации: {e}"
 
-with gr.Blocks(title="🧠 Eroha Summarizer PRO v4.0") as app:
-    gr.Markdown("## 🧠 **Eroha Summarizer PRO** — Multilingual Summarizer (BART / MBART / mT5)")
+# --- UI ---
+with gr.Blocks(title="Eroha Summarizer PRO — Multilingual (BART / MBART / mT5)") as app:
+    gr.Markdown("""
+    ## 🧠 **Eroha Summarizer PRO**
+    <div style='color:gray'>Многоязычный суммаризатор (EN/RU/Multilingual)</div>
+    """)
     status = gr.Markdown(status_message)
     inp = gr.Textbox(label="Введите текст", lines=12, placeholder="Вставьте текст сюда...")
     out = gr.Textbox(label="Результат суммаризации")